Dissertationen zum Thema „Réseaux sociaux (Internet) – Analyse informatique“
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Mezghani, Manel. „Analyse des réseaux sociaux : vers une adaptation de la navigation sociale“. Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30127/document.
Der volle Inhalt der QuelleThe advent of Web 2.0, user-centered, has given rise to a significant amount of information (personal, collective, shared, "loved", etc.). This information is a way to help users and guide them to the information sought. However, this quantity makes access to shared information more and more difficult, given the diversity of content that may interest the user. Disorientation of the user is one of the main problems related to social media. To overcome such problem, adaptation is a standard solution that can be applied in a social context. With the evolution of these social networks, new concepts appear such as social navigation, which is a way to navigate while being influenced by other users in the network: Another important concept is that of "tag". This term is defined as social annotations created by users and associated to resources. Navigation can be therefore carried out by both links and tags. Adapting social navigation means making it more targeted for each user according to their interests. In practice, this can be done by recommending tags to each user, so he can follow or not. To adapt the social navigation, we must ensure proper detection of the user's interests and taking into account their evolution. However, we are faced with some problems: i) the detection of interest, since they can be derived from several social resources (friends, resources, tags, etc.). Their relevance is primordial to ensure adequate adaptation result. ii) updating the user profile. Indeed, the social user, is characterized by its great social activity, and therefore its interests should reflect its "real" interest each time period in order to achieve a reliable adaptation. To solve the problems affecting the quality of adaptation of social navigation quoted above, we first proposed a method for detecting the user's interests. This proposal aims to overcome the detection of irrelevant interests issues. This approach analyzes the user tags depending on the content of their respective resources. Unlike most research, who do not consider the accuracy of tags with the contents of resource, the accuracy reflects whether the user is really interested with the content or not. This is done by querying the user's network and analysis of the user annotation behavior. The approach is based on the assumption that a user annotates the resource by tags reflecting the content of this resource better reflects its "true" interests. Following the proposal of the interests of detection approach, we conducted second, the treatment of the problem of updating these interests. We were interested to the user profile enrichment techniques, performed by adding interests deemed relevant at a given time. The enrichment in a social context is performed according to social information such as neighbours who share the user behaviors in common, according to the user annotation behavior, and according to the metadata annotated resources. The choice of such information shall follow the study of their influence on the changing interests of the user. The approach we used enrichment propose recommendations (tags) according to the new tags added to the user profile. Both contributions were tested on the social database Delicious. They showed a sizeable accuracy rate. They have also proven their efficiency compared to conventional methods. In addition, the rate of ambiguity associated with the tags has been greatly reduced, thanks to the implicit filtering of irrelevant tags relative to resource content
Perez, Charles. „Approche comportementale pour la sécurisation des utilisateurs de réseaux sociaux numériques mobiles“. Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0019/document.
Der volle Inhalt der QuelleOur society is facing many changes in the way it communicates. The emergence of mobile terminals alongside digital social networks allows information to be shared from almost anywhere with the option of all parties being connected simultaneously. The growing use of smartphones and digital social networks in a professional context presents an opportunity, but it also exposes businesses and users to many threats, such as leakage of sensitive information, spamming, illegal access to personal data, etc.Although a significant increase in malicious activities on social platforms can be observed, currently there is no solution that ensures a completely controlled usage of digital social networks. This work aims to make a major contribution in this area through the implementation of a methodology (SPOTLIGHT) that not only uses the behaviour of profiles for evaluation purposes, but also to protect the user. This methodology relies on the assumption that smartphones, which are closely related to their owners, store and memorise traces of activity (interactions) that can be used to better protect the user online.This approach is implemented in a mobile prototype called SPOTLIGHT 1.0, which analyses traces stored in users’ smartphone to help them make the right decisions to protect their data
Sha, Xiaolan. „Personnalisation du contenu et tendances dans les médias sociaux“. Electronic Thesis or Diss., Paris, ENST, 2013. http://www.theses.fr/2013ENST0026.
Der volle Inhalt der QuelleFluctuating along user connections, some content succeeds at capturing the attention of a large amount of users and suddenly becomes trending. Understanding trending content and its dynamics is crucial to the explanation of opinion spreading, and to the design of social marketing strategies. While previous research has mostly focused on trending content and on the network structure of individuals in social media, this work complements these studies by exploring in depth the human factors behind the generation of this content. We build upon this analysis to investigate new personalization tools helping individuals to discover interesting social media content. This work contributes to the literature on the following aspects: an in depth analysis on individuals who create trending content in social media that uncovers their distinguishing characteristics; a novel means to identify trending content by relying on the ability of special individuals who create them; a mechanism to build a recommender system to personalize trending content; and techniques to improve the quality of recommendations beyond the core theme of accuracy. Our studies underline the vital role of special users in the creation of trending content in social media. Thanks to such special users and their ``wisdom'', individuals may discover the trending content distilled to their tastes. Our work brings insights in two main research directions - trending content in social media and recommender systems
Abid, Younes. „Analyse automatisée des risques sur la vie privée dans les réseaux sociaux“. Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0088/document.
Der volle Inhalt der QuelleIn this thesis we shed the light on the danger of privacy leakage on social network. We investigate privacy breaches, design attacks, show their feasibility and study their accuracies. This approach helps us to track the origin of threats and is a first step toward designing effective countermeasures. We have first introduced a subject sensitivity measure through a questionnaire survey. Then, we have designed on-line friendship and group membership link disclosure (with certainty) attacks on the largest social network “Facebook”. These attacks successfully uncover the local network of a target using only legitimate queries. We have also designed sampling techniques to rapidly collect useful data around a target. The collected data are represented by social-attribute networks and used to perform attribute inference (with uncertainty) attacks. To increase the accuracy of attacks, we have designed cleansing algorithms. These algorithms quantify the correlation between subjects, select the most relevant ones and combat data sparsity. Finally, we have used a shallow neural network to classify the data and infer the secret values of a sensitive attribute of a given target with high accuracy measured by AUC on real datasets. The proposed algorithms in this work are included in a system called SONSAI that can help end users analyzing their local network to take the hand over their privacy
Rakoczy, Monika. „Exploring human interactions for influence modeling in online social networks“. Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL010/document.
Der volle Inhalt der QuelleOnline social networks are constantly growing in popularity. They enable users to interact with one another and shifting their relations to the virtual world. Users utilize social media platforms as a mean for a rich variety of activities. Indeed, users are able to express their opinions, share experiences, react to other users' views and exchange ideas. Such online human interactions take place within a dynamic hierarchy where we can observe and distinguish many qualities related to relations between users, concerning influential, trusted or popular individuals. In particular, influence within Social Networks (SN) has been a recent focus in the literature. Many domains, such as recommender systems or Social Network Analysis (SNA), measure and exploit users’ influence. Therefore, models discovering and estimating influence are important for current research and are useful in various disciplines, such as marketing, political and social campaigns, recommendations and others. Interestingly, interactions between users can not only indicate influence but also involve trust, popularity or reputation of users. However, all these notions are still vaguely defined and not meeting the consensus in the SNA community. Defining, distinguishing and measuring the strength of those relations between the users are also posing numerous challenges, on theoretical and practical ground, and are yet to be explored. Modelization of influence poses multiple challenges. In particular, current state-of-the-art methods of influence discovery and evaluation still do not fully explore users’ actions of various types, and are not adaptive enough for using different SN. Furthermore, adopting the time aspect into influence model is important, challenging and in need of further examination part of the research. Finally, exploring possible connections and links between coinciding notions, like influence and reputation, remains to be performed.In this thesis, we focus on the qualities of users connected to four important concepts: influence, reputation, trust, and popularity, in the scope of SNA for influence modeling. We analyze existing works utilizing these notions and we compare and contrast their interpretations. Consequently, we emphasize the most important features that these concepts should include and we make a comparative analysis of them. Accordingly, we present a global classification of the notions concerning their abstract level and distinction of the terms from one another, which is a first and required contribution of the thesis. Consequently, we then propose a theoretical model of influence and present influence-related ontology. We also present a distinction of notion not yet explored in SNA discipline -- micro-influence, which targets new phenomena of users with a small but highly involved audience, who are observed to be still highly impactful. Basing on the definitions of the concepts, we propose a practical model, called Action-Reaction Influence Model (ARIM). This model considers type, quality, quantity, and frequency of actions performed by users in SN, and is adaptive to different SN types. We also focus on the quantification of influence over time and representation of influence causal effect. In order to do that, we focus on a particular SN with a specific characteristic - citation network. Indeed, citation networks are particularly time sensitive. Accordingly, we propose Time Dependent Influence Estimation (TiDIE), a model for determining influence during a particular time period between communities within time-dependent citation networks. Finally, we also combine two of the abovementioned notions, influence and reputation, in order to investigate the dependencies between them. In particular, we propose a transition method, ReTiDIE, that uses influence for predicting the reputation. For each of the proposed approaches, experiments have been conducted on real-world datasets and demonstrate the suitability of the methods
Sha, Xiaolan. „Personnalisation du contenu et tendances dans les médias sociaux“. Thesis, Paris, ENST, 2013. http://www.theses.fr/2013ENST0026/document.
Der volle Inhalt der QuelleFluctuating along user connections, some content succeeds at capturing the attention of a large amount of users and suddenly becomes trending. Understanding trending content and its dynamics is crucial to the explanation of opinion spreading, and to the design of social marketing strategies. While previous research has mostly focused on trending content and on the network structure of individuals in social media, this work complements these studies by exploring in depth the human factors behind the generation of this content. We build upon this analysis to investigate new personalization tools helping individuals to discover interesting social media content. This work contributes to the literature on the following aspects: an in depth analysis on individuals who create trending content in social media that uncovers their distinguishing characteristics; a novel means to identify trending content by relying on the ability of special individuals who create them; a mechanism to build a recommender system to personalize trending content; and techniques to improve the quality of recommendations beyond the core theme of accuracy. Our studies underline the vital role of special users in the creation of trending content in social media. Thanks to such special users and their ``wisdom'', individuals may discover the trending content distilled to their tastes. Our work brings insights in two main research directions - trending content in social media and recommender systems
Chouchani, Nadia. „Une approche de détection des communautés d'intérêt dans les réseaux sociaux : application à la génération d'IHM personnalisées“. Thesis, Valenciennes, 2018. http://www.theses.fr/2018VALE0048/document.
Der volle Inhalt der QuelleNowadays, Social Networks are ubiquitous in all aspects of life. A fundamental feature of these networks is the connection between users. These are gradually engaged to contribute by adding their own content. So Social Networks also integrate user creations ; which encourages researchers to revisit the methods of their analysis. This field has now led to a great deal of research in recent years. One of the main problems is the detection of communities. The research presented in this thesis is positioned in the themes of the semantic analysis of Social Networks and the generation of personalized interactive applications. This thesis proposes an approach for the detection of communities of interest in Social Networks. This approach models social data in the form of a social user profile represented by an ontology. It implements a method for the Sentiment Analysis based on the phenomena of social influence and homophily. The detected communities are exploited in the generation of personalized interactive applications. This generation is based on an approach of type MDA, independent of the application domain. In addition, this manuscript reports an evaluation of our proposals on data from Real Social Networks
Tchuente, Dieudonné. „Modélisation et dérivation de profils utilisateurs à partir de réseaux sociaux : approche à partir de communautés de réseaux k-égocentriques“. Toulouse 3, 2013. http://thesesups.ups-tlse.fr/1972/.
Der volle Inhalt der QuelleIn most systems that require user modeling to adapt information to each user's specific need, a user is usually represented by a user profile in the form of his interests. These interests are learnt and enriched over time from users interactions with the system. By the evolving nature of user's interests, the user's profile can never be considered fully known by a system. This partial knowledge of the user profile at any time t significantly reduces the performance of adaptive systems, when the user's profile contains no or only some information. This drawback is particularly most recurrent for new users in a system (time t = 0, also called cold start problem) and for less active users. To address this problem, several studies have explored data sources other than those produced by the user in the system: activities of users with similar behavior (e. G. Collaborative filtering techniques) or data generated by the user in other systems (e. G. , multi-application user's profiles, multiple identities management systems). By the recent advent of Social Web and the explosion of online social networks sites, social networks are more and more studied as an external data source that can be used to enrich users' profiles. This has led to the emergence of new social information filtering techniques (e. G. Social information retrieval, social recommender systems). Current studies on social information filtering show that this new research field is very promising. However, much remains to be done to complement and enhance these studies. We particularly address two drawbacks: (i) each existing social information filtering approach is specific in its field scope (and associated mechanisms), (ii) these approaches unilaterally use profiles of individuals around the user in the social network to improve traditional information filtering systems. To overcome these drawbacks in this thesis, we aim at defining a generic social model of users' profiles that can be reusable in many application domains and for several social information filtering mechanisms, and proposing optimal techniques for enriching user's profile from the user's social network. We rely on existing studies in social sciences to propose a communities (rather than individuals) based approach for using individuals around the user in a specific part of his social network, to derive his social profile (profile that contains user's interest derived from his social network). The significant part of the user's social network used in our studies is composed of individuals located at a maximum distance k (in the entire social network) from the user, and relationships between these individuals (k-egocentric network). Two evaluations of the proposed approach based on communities in k-egocentric networks have been conducted in the online social network Facebook and the co-authors network DBLP. They allow us to demonstrate the relevance of the proposal with respect to existing individual based approaches, and the impact of structural measures such as the centrality of communities (degree or proximity) or user's k-egocentric network density, on the quality of results. Our approach opens up many opportunities for future studies in social information filtering and many application domains as well as on the Web (e. G. Personalization of search engines, recommender systems in e-commerce, adaptive systems in e-Learning environment) or in Intranets business systems (e. G. Behavioral analysis in networks of subscribers telecom customers, detection of abnormal behavior network bank customers, etc. )
Gilbert, Frédéric. „Méthodes et modèles pour la visualisation de grandes masses de données multidimensionnelles nominatives dynamiques“. Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14498/document.
Der volle Inhalt der QuelleSince ten years, informations visualization domain knows a real interest.Recently, with the growing of communications, the research on social networks analysis becomes strongly active. In this thesis, we present results on dynamic social networks analysis. That means that we take into account the temporal aspect of data. We were particularly interested in communities extraction within networks and their evolutions through time. [...]
García, Recuero Álvaro. „Discouraging abusive behavior in privacy-preserving decentralized online social networks“. Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S010/document.
Der volle Inhalt der QuelleThe main goal of this thesis is to evaluate privacy-preserving protocols to detect abuse in future decentralised online social platforms or microblogging services, where often limited amount of metadata is available to perform data analytics. Taking into account such data minimization, we obtain acceptable results compared to techniques of machine learning that use all metadata available. We draw a series of conclusion and recommendations that will aid in the design and development of a privacy-preserving decentralised social network that discourages abusive behavior
Poulain, Rémy. „Analyse et modélisation de la diversité des structures relationnelles à l'aide de graphes multipartis“. Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS453.
Der volle Inhalt der QuelleThere is no longer any need to prove that digital technology, the Internet and the web have led to a revolution, particularly in the way people get information. Like any revolution, it is followed by a series of issues : equal treatment of users and suppliers, ecologically sustainable consumption, freedom of expression and censorship, etc. Research needs to provide a clear vision of these stakes. Among these issues, we can talk about two phenomena : the echo chamber phenomenon and the filter bubble phenomenon. These two phenomena are linked to the lack of diversity of information visible on the Internet, and one may wonder about the impact of recommendation algorithms. Even if this is our primary motivation, we are moving away from this subject to propose a general scientific framework to analyze diversity. We find that the graph formalism is useful enough to be able to represent relational data. More precisely, we will analyze relational data with entities of different natures. This is why we chose the n-part graph formalism because this is a good way to represent a great diversity of data. Even if the first data we studied is related to recommendation algorithms (music consumption or purchase of articles on a platform) we will see over the course of the manuscript how this formalism can be adapted to other types of data (politicized users on Twitter, guests of television shows, establishment of NGOs in different States ...). There are several objectives in this study : — Mathematically define diversity indicators on the n-part graphs. — Algorithmically define how to calculate them. — Program these algorithms to make them a usable computer object. — Use these programs on quite varied data. — See the different meanings that our indicators can have. We will begin by describing the mathematical formalism necessary for our study. Then we will apply our mathematical object to basic examples to see all the possibilities that our object offers us. This will show us the importance of normalizing our indicators, and will motivate us to study random normalization. Then we will see another series of examples which will allow us to go further on our indicators, going beyond the static and tripartite side to approach graphs with more layers and depending on time. To be able to have a better vision of what the real data brings us, we will study our indicators on completely randomly generated graphs
Renoust, Benjamin. „Analysis and Visualisation of Edge Entanglement in Multiplex Networks“. Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00942358.
Der volle Inhalt der QuelleCombe, David. „Détection de communautés dans les réseaux d'information utilisant liens et attributs“. Phd thesis, Université Jean Monnet - Saint-Etienne, 2013. http://tel.archives-ouvertes.fr/tel-01056985.
Der volle Inhalt der QuelleDeparis, Etienne. „Création de nouvelles connaissances décisionnelles pour une organisation via ses ressources sociales et documentaires“. Phd thesis, Université de Technologie de Compiègne, 2013. http://tel.archives-ouvertes.fr/tel-01016788.
Der volle Inhalt der QuelleHenry, Didier. „Modèles de propagation de l'information et méthodes de sciences des données“. Thesis, Antilles, 2018. http://www.theses.fr/2018ANTI0323/document.
Der volle Inhalt der QuelleNowadays, online social media has transformed the way we create, share and access information. These platforms rely on gigantic networks that promote the free exchange of information between hundreds of millions of people around the world, and this instantly.Whether related to a global event or in connection with a local event, these messages may influence a society and may contain information useful for the detection or prediction of real-world phenomena.However, some broadcast messages can have a very negative impact in real life. These messages containing false information can have disastrous consequences.To avoid and anticipate these dramatic situations, follow rumors, avoid bad reputations, it is necessary to study and then model the propagation of information.However, most of the diffusion models introduced are based on axiomatic hypotheses represented by mathematical models. As a result, these models are far removed from the users' dissemination behaviors in that they do not incorporate observations made on concrete dissemination cases. In our work, we study the phenomenon of diffusion of information at two scales. On a microscopic scale, we observed diffusion behaviors based on the personality traits of users by analyzing the messages they post in terms of feelings and emotions. On a macroscopic scale, we analyzed the evolution of the diffusion phenomenon by taking into account the geographical dimension of the users
Cambe, Jordan. „Understanding the complex dynamics of social systems with diverse formal tools“. Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEN043/document.
Der volle Inhalt der QuelleFor the past two decades, electronic devices have revolutionized the traceability of social phenomena. Social dynamics now leave numerical footprints, which can be analyzed to better understand collective behaviors. The development of large online social networks (like Facebook, Twitter and more generally mobile communications) and connected physical structures (like transportation networks and geolocalised social platforms) resulted in the emergence of large longitudinal datasets. These new datasets bring the opportunity to develop new methods to analyze temporal dynamics in and of these systems. Nowadays, the plurality of data available requires to adapt and combine a plurality of existing methods in order to enlarge the global vision that one has on such complex systems. The purpose of this thesis is to explore the dynamics of social systems using three sets of tools: network science, statistical physics modeling and machine learning. This thesis starts by giving general definitions and some historical context on the methods mentioned above. After that, we show the complex dynamics induced by introducing an infinitesimal quantity of new agents to a Schelling-like model and discuss the limitations of statistical model simulation. The third chapter shows the added value of using longitudinal data. We study the behavior evolution of bike sharing system users and analyze the results of an unsupervised machine learning model aiming to classify users based on their profiles. The fourth chapter explores the differences between global and local methods for temporal community detection using scientometric networks. The last chapter merges complex network analysis and supervised machine learning in order to describe and predict the impact of new businesses on already established ones. We explore the temporal evolution of this impact and show the benefit of combining networks topology measures with machine learning algorithms
Leprovost, Damien. „Découverte et analyse des communautés implicites par une approche sémantique en ligne : l'outil WebTribe“. Phd thesis, Université de Bourgogne, 2012. http://tel.archives-ouvertes.fr/tel-00866489.
Der volle Inhalt der QuelleHeymann, Sébastien. „Analyse exploratoire de flots de liens pour la détection d'événements“. Phd thesis, Université Pierre et Marie Curie - Paris VI, 2013. http://tel.archives-ouvertes.fr/tel-00994766.
Der volle Inhalt der QuelleHammoud, Khodor. „Trust in online data : privacy in text, and semantic-based author verification in micro-messages“. Electronic Thesis or Diss., Université Paris Cité, 2021. http://www.theses.fr/2021UNIP5203.
Der volle Inhalt der QuelleMany Problems surround the spread and use of data on social media. There is a need to promote trust on social platforms, regarding the sharing and consumption of data. Data online is mostly in textual form which poses challenges for automation solutions because of the richness of natural language. In addition, the use of micro-messages as the main means of communication on social media makes the problem much more challenging because of the scarceness of features to analyze per body of text. Our experiments show that data anonymity solutions cannot preserve user anonymity without sacrificing data quality. In addition, in the field of author verification, which is the problem of determining if a body of text was written by a specific person or not, given a set of documents known to be authored by them, we found a lack of research working with micro-messages. We also noticed that the state-of-the-art does not take text semantics into consideration, making them vulnerable to impersonation attacks. Motivated by these findings, we devote this thesis to tackle the tasks of (1) identifying the current problems with user data anonymity in text, and provide an initial novel semantic-based approach to tackle this problem, (2) study author verification in micro-messages and identify the challenges in this field, and develop a novel semantics-based approach to solve these challenges, and (3) study the effect of including semantics in handling manipulation attacks, and the temporal effect of data, where the authors might have changing opinions over time. The first part of the thesis focuses on user anonymity in textual data, with the aim to anonymize personal information from online user data for safe data analysis without compromising users’ privacy. We present an initial novel semantic-based approach, which can be customized to balance between preserving data quality and maximizing user anonymity depending on the application at hand. In the second part, we study author verification in micro-messages on social media. We confirm the lack of research in author verification on micro-messages, and we show that the state-of-the-art, which primarily handles long and medium-sized texts, does not perform well when applied on micro-messages. Then we present a semantics-based novel approach which uses word embeddings and sentiment analysis to collect the author’s opinion history to determine the correctness of the claim of authorship, and show its competitive performance on micro-messages. We use these results in the third part of the thesis to further improve upon our approach. We construct a dataset consisting of the tweets of the 88 most followed twitter influencers. We use it to show that the state-of-the-art is not able to handle impersonation attacks, where the content of a tweet is altered, changing the message behind the tweet, while the writing pattern is preserved. On the other hand, since our approach is aware of the text’s semantics, it is able to detect text manipulations with an accuracy above 90%. And in the fourth part of the thesis, we analyze the temporal effect of data on our approach for author verification. We study the change of authors’ opinions over time, and how to accommodate for that in our approach. We study trends of sentiments of an author per a specific topic over a period of time, and predict false authorship claims depending on what timeframe does the claim of authorship fall in
Abdallah, Raed. „Intelligent crime detection and behavioral pattern mining : a comprehensive study“. Electronic Thesis or Diss., Université Paris Cité, 2023. http://www.theses.fr/2023UNIP7031.
Der volle Inhalt der QuelleIn the face of a rapidly evolving criminal landscape, law enforcement agencies (LEAs) grapple with escalating challenges in contemporary criminal investigations. This PhD thesis embarks on a transformative exploration, encouraged by an urgent need to revolutionize investigative methodologies and arm LEAs with state-of-the-art tools to combat crime effectively. Rooted in this imperative motivation, the research meticulously navigates diverse data sources, including the intricate web of social media networks, omnipresent video surveillance systems, and expansive online platforms, recognizing their fundamental roles in modern crime detection. The contextual backdrop of this research is the pressing demand to empower LEAs with advanced capabilities in intelligent crime detection. The surge in digital interactions necessitates a paradigm shift, compelling researchers to delve deep into the labyrinth of social media, surveillance footage, and online data. This context underscores the urgency to fortify law enforcement strategies with cutting-edge technological solutions. Motivated by urgency, the thesis focuses on three core objectives: firstly, automating suspect identification through the integration of data science, big data tools, and ontological models, streamlining investigations and empowering law enforcement with advanced inference rules; secondly, enabling real-time detection of criminal events within digital noise via intricate ontological models and advanced inference rules, providing actionable intelligence and supporting informed decision-making for law enforcement; and thirdly, enhancing video surveillance by integrating advanced deep learning algorithms for swift and precise detection of knife-related crimes, representing a pioneering advancement in video surveillance technology. Navigating this research terrain poses significant challenges. The integration of heterogeneous data demands robust preprocessing techniques, enabling the harmonious fusion of disparate data types. Real-time analysis of social media intricacies necessitates ontological models adept at discerning subtle criminal nuances within the digital tapestry. Moreover, designing Smart Video Surveillance Systems necessitates the fusion of state-of-the-art deep learning algorithms with real-time video processing, ensuring both speed and precision in crime detection. Against these challenges, the thesis contributes innovative solutions at the forefront of contemporary crime detection technology. The research introduces ICAD, an advanced framework automating suspect identification and revolutionizing investigations. CRI-MEDIA tackles social media crime challenges using a streamlined process and enriched criminal ontology. Additionally, SVSS, a Smart Video Surveillance System, swiftly detects knife-related crimes, enhancing public safety. Integrating ICAD, CRI-MEDIA, and SVSS, this work pioneers intelligent crime detection, empowering law enforcement with unprecedented capabilities in the digital age. Critical to the integrity of the research, the proposed methodologies undergo rigorous experimentation in authentic criminal scenarios. Real-world data gathered from actual investigations form the crucible wherein ICAD, CRI-MEDIA, and SVSS are tested. These experiments serve as a litmus test, affirming not only the viability of the proposed solutions but also offering nuanced insights for further refinement. The results underscore the practical applicability of these methodologies, their adaptability in diverse law enforcement contexts, and their role in enhancing public safety and security
Walczak, Nathalie. „La protection des données personnelles sur l’internet.- Analyse des discours et des enjeux sociopolitiques“. Thesis, Lyon 2, 2014. http://www.theses.fr/2014LYO20052/document.
Der volle Inhalt der QuelleThis thesis, in Communication and Information Sciences, raises the question of the internet personal data protection through the discourses analysis of four actors concerned with this subject: internet companies, authorities regulating, French population and national press. The objective is to understand how, through the discourses of each one of these actors, the question of the jamming of the spheres private and public about the Internet takes shape. It is a question which increases with the development of the Internet, in particular with the multiplication of the social digital network, which gives to the Internet users various opportunities to display their privacy. The multiplication of the interpersonal relationship devices connection is then accompanied by a contemporary dialectical between private and public spheres, not always controlled by concerned people.This interaction between private and public leads to a transfert of the border wich separates the two spheres and can involves some drifts on behalf of specialized companies, such Google and Facebook, toward the aggregation of personal data contents. Indeed, databases are central in the economic system of these companies and gained a commercial value. However, the commercial use as of these data is not necessarily known by the user and can be realized without its agreement, at least in an explicit way. This double questioning related to the jamming of the private and public spheres, i.e., firstly, the individual aspect where the Internet user is incited to reveal personal elements more and more, and, secondly, the related aspect with the selling of the data by the Internet companies, then generates the question of the individual freedom and data confidentiality. The regulating authorities, in France or in European Union, try to provide answers in order to protect the Internet users by setting up actions relating to the right to be forgotten or by prosecuting Google, for example, when the company does not conform to the laws in force on the territory concerned. The various angles of incidence as well as the diversity of the studied actors required the constitution of a multidimentional corpus in order to have a comparative approach of the different representations. This corpus includes texts registered like political discourses, regulating authorities speeches, companies of the Internet speeches, specifically Google and Facebook, or press speeches which occupy a meta-discursive position since they repeat speeches of the actors previously stated. It includes also oral speeches made up of talks especially recorded for this research with some persons taken randomly in the French population. A quantitative analysis of the discourses between 2010 and 2013, contemporary period with the thesis, permit to carry out a first sorting and to select only the most relevant speeches compared to our hypothesis. The qualitative analysis which followed was based on the theoretical framework previously elaborate in order to cross the representations of the actors in connection with the personal data and to highlight the various visions about this question
Praboda, Chathurangani Rajapaksha Rajapaksha Waththe Vidanelage. „Clickbait detection using multimodel fusion and transfer learning“. Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAS025.
Der volle Inhalt der QuelleInternet users are likely to be victims to clickbait assuming as legitimate news. The notoriety of clickbait can be partially attributed to misinformation as clickbait use an attractive headline that is deceptive, misleading or sensationalized. A major type of clickbait are in the form of spam and advertisements that are used to redirect users to web sites that sells products or services (often of dubious quality). Another common type of clickbait are designed to appear as news headlines and redirect readers to their online venues intending to make revenue from page views, but these news can be deceptive, sensationalized and misleading. News media often use clickbait to propagate news using a headline which lacks greater context to represent the article. Since news media exchange information by acting as both content providers and content consumers, misinformation that is deliberately created to mislead requires serious attention. Hence, an automated mechanism is required to explore likelihood of a news item being clickbait.Predicting how clickbaity a given news item is difficult as clickbait are very short messages and written in obscured way. The main feature that can identify clickbait is to explore the gap between what is promised in the social media post, news headline and what is delivered by the article linked from it. The recent enhancement to Natural Language Processing (NLP) can be adapted to distinguish linguistic patterns and syntaxes among social media post, news headline and news article.In my Thesis, I propose two innovative approaches to explore clickbait generated by news media in social media. Contributions of my Thesis are two-fold: 1) propose a multimodel fusion-based approach by incorporating deep learning and text mining techniques and 2) adapt Transfer Learning (TL) models to investigate the efficacy of transformers for predicting clickbait contents.In the first contribution, the fusion model is built on using three main features, namely similarity between post and headline, sentiment of the post and headline and topical similarity between news article and post. The fusion model uses three different algorithms to generate output for each feature mentioned above and fuse them at the output to generate the final classifier.In addition to implementing the fusion classifier, we conducted four extended experiments mainly focusing on news media in social media. The first experiment is on exploring content originality of a social media post by amalgamating the features extracted from author's writing style and online circadian rhythm. This originality detection approach is used to identify news dissemination patterns among news media community in Facebook and Twitter by observing news originators and news consumers. For this experiment, dataset is collected with our implemented crawlers from Facebook and Twitter streaming APIs. The next experiment is on exploring flaming events in the news media in Twitter by using an improved sentiment classification model. The final experiment is focused on detecting topics that are discussed in a meeting real-time aiming to generate a brief summary at the end.The second contribution is to adapt TL models for clickbait detection. We evaluate the performance of three TL models (BERT, XLNet and RoBERTa) and delivered a set of architectural changes to optimize these models.We believe that these models are the representatives of most of the other TL models in terms of their architectural properties (Autoregressive model vs Autoencoding model) and training datasets. The experiments are conducted by introducing advanced fine-tuning approaches to each model such as layer pruning, attention pruning, weight pruning, model expansion and generalization. To the best of authors' knowledge, there have been an insignificant number of attempts to use TL models on clickbait detection tasks and no any comparative analysis of multiple TL models focused on this task
Yang, Dingqi. „Understanding human dynamics from large-scale location-centric social media data : analysis and applications“. Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0002.
Der volle Inhalt der QuelleHuman dynamics is an essential aspect of human centric computing. As a transdisciplinary research field, it focuses on understanding the underlying patterns, relationships, and changes of human behavior. By exploring human dynamics, we can understand not only individual’s behavior, such as a presence at a specific place, but also collective behaviors, such as social movement. Understanding human dynamics can thus enable various applications, such as personalized location based services. However, before the availability of ubiquitous smart devices (e.g., smartphones), it is practically hard to collect large-scale human behavior data. With the ubiquity of GPS-equipped smart phones, location based social media has gained increasing popularity in recent years, making large-scale user activity data become attainable. Via location based social media, users can share their activities as real-time presences at Points of Interests (POIs), such as a restaurant or a bar, within their social circles. Such data brings an unprecedented opportunity to study human dynamics. In this dissertation, based on large-scale location centric social media data, we study human dynamics from both individual and collective perspectives. From individual perspective, we study user preference on POIs with different granularities and its applications in personalized location based services, as well as the spatial-temporal regularity of user activities. From collective perspective, we explore the global scale collective activity patterns with both country and city granularities, and also identify their correlations with diverse human cultures
Debaere, Steven. „Proactive inferior member participation management in innovation communities“. Thesis, Lille, 2018. http://www.theses.fr/2018LIL1A012.
Der volle Inhalt der QuelleNowadays, companies increasingly recognize the benefits of innovation communities (ICs) to inject external consumer knowledge into innovation processes. Despite the advantages of ICs, guaranteeing the viability poses two important challenges. First, ICs are big data environments that can quickly overwhelm community managers as members communicate through posts, thereby creating substantial (volume), rapidly expanding (velocity), and unstructured data that might encompass combinations of linguistic, video, image, and audio cues (variety). Second, most online communities fail to generate successful outcomes as they are often unable to derive value from individual IC members owing to members’ inferior participation. This doctoral dissertation leverages customer relationship management strategies to tackle these challenges and adds value by introducing a proactive inferior member participation management framework for community managers to proactively reduce inferior member participation, while effectively dealing with the data-rich IC environment. It proves that inferior member participation can be identified proactively by analyzing community actors’ writing style. It shows that dependencies between members’ participation behaviour can be exploited to improve prediction performance. Using a field experiment, it demonstrates that a proactive targeted email campaign allows to effectively reduce inferior member participation
Portilla, Yonathan. „Etude des Réseaux Sociaux : modélisation et analyse“. Thesis, Avignon, 2019. http://www.theses.fr/2019AVIG0235.
Der volle Inhalt der QuelleCurrently social networks focus on the sharing and exchange of opinions, videos, photos, music,news and others informations, one of its objectives is to establish direct and indirect linkswith users. Social networks also promote products, people (their political or artistic image) orinfluential brands.Social networks are changing rapidly, so we’re looking to see the evolution of these sharingtools, and see how social networks change over time.We have the opportunity to study the events that occur in social networks thanks to the amount ofdata they produce. In the current market there are tools that allow the analysis of social networks,but most tools are not free, and 100% free tools disappear over time. For this reason we decidedto produce computer tools able to extract and analyse the data of the social networks studied.This study begins with the state of the art, where we describe the context of the problem, thework that led to this study and a summary of the contributions made during the thesis that wepresent briefly in the rest of the abstract.i. First we focus on the geo-linguistic fingerprint and language evolution in Twitter. Accessto content of messages sent by a group of subscribers of a social network may be usedto identify and quantify some features of a group. The feature can represent the level ofinterest in an event or product, or the popularity of an idea, or of a musical hit, or of apolitical figure. The feature can also represent how language is used and transformed,how words are written and how new grammatical rules appear.ii. Then we study the evolution of the cultural phenomenon called meme in social networks.Memes were defined by R. Dowkins as a cultural phenomenon that spreads through nongeneticforms. We examine three of the most popular memes of the internet and examinetheir impact on society in the Mediterranean countries. We use for analysing Google Trends, Topsy (a tool to measure the popularity of words on Twitter) and YouTube toquantify the impact of memes in the Mediterranean society.iii. After that we study the YouTube recommendation graph based on measurements andstochastic tools. We confirm that recommendation lists influence the views of a video.We focus on the recommendation system that boosts the popularity of videos. We buildfirst a graph that captures the recommendation system in YouTube and we study the relationshipbetween the number of views of a video and the average number of views of avideo in its recommendation list.iv. To conclude we describe the online tools available and the tools that we developed duringthe thesis. The online tools Topsy, Trendistic and Google Trends allowed us to analyseplatforms like YouTube and Twitter. We also produced tools based on API’s: in Twitterwe used the Streaming function to download and analyse tweets, with the Topsy APIwe studied the evolution of the language and the use of words, and the YouTube’s APIsallowed us to describe the behaviour on the lists of recommendations and the popularityof videos
Yang, Dingqi. „Understanding human dynamics from large-scale location-centric social media data : analysis and applications“. Thesis, Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0002/document.
Der volle Inhalt der QuelleHuman dynamics is an essential aspect of human centric computing. As a transdisciplinary research field, it focuses on understanding the underlying patterns, relationships, and changes of human behavior. By exploring human dynamics, we can understand not only individual’s behavior, such as a presence at a specific place, but also collective behaviors, such as social movement. Understanding human dynamics can thus enable various applications, such as personalized location based services. However, before the availability of ubiquitous smart devices (e.g., smartphones), it is practically hard to collect large-scale human behavior data. With the ubiquity of GPS-equipped smart phones, location based social media has gained increasing popularity in recent years, making large-scale user activity data become attainable. Via location based social media, users can share their activities as real-time presences at Points of Interests (POIs), such as a restaurant or a bar, within their social circles. Such data brings an unprecedented opportunity to study human dynamics. In this dissertation, based on large-scale location centric social media data, we study human dynamics from both individual and collective perspectives. From individual perspective, we study user preference on POIs with different granularities and its applications in personalized location based services, as well as the spatial-temporal regularity of user activities. From collective perspective, we explore the global scale collective activity patterns with both country and city granularities, and also identify their correlations with diverse human cultures
Stoica, Beck Alina. „Analyse de la structure locale des grands réseaux sociaux“. Phd thesis, Université Paris-Diderot - Paris VII, 2010. http://tel.archives-ouvertes.fr/tel-00987880.
Der volle Inhalt der QuellePietiläinen, Anna-Kaisa. „Opportunistic mobile social networks at work“. Paris 6, 2010. http://www.theses.fr/2010PA066587.
Der volle Inhalt der QuelleCutillo, Leucio Antonio. „Protection des données privées dans les réseaux sociaux“. Electronic Thesis or Diss., Paris, ENST, 2012. http://www.theses.fr/2012ENST0020.
Der volle Inhalt der QuelleOnline Social Network (OSN) applications allow users of all ages and educational background to easily share a wide range of personal information with a theoretically unlimited number of partners. This advantage comes at the cost of increased security and privacy exposures for users, since in all existing OSN applications, to underpin a promising business model, users' data is collected and stored permanently at the databases of the service provider, which potentially becomes a “Big Brother” capable of exploiting this data in many ways that can violate the privacy of individual users or user groups. This thesis suggests and validates a new approach to tackle these security and privacy problems. In order to ensure users' privacy in the face of potential privacy violations by the provider, the suggested approach adopts a distributed architecture relying on cooperation among a number of independent parties that are also the users of the online social network application. The second strong point of the suggested approach is to capitalize on the trust relationships that are part of social networks in real life in order to cope with the problem of building trusted and privacy-preserving mechanisms as part of the online application. Based on these main design principles, a new distributed Online Social Network, namely Safebook, is proposed: Safebook leverages on real life trust and allows users to maintain the control on the access and the usage of their own data. The prototype of Safebook is available at www.safebook.eu
Cutillo, Leucio Antonio. „Protection des données privées dans les réseaux sociaux“. Phd thesis, Télécom ParisTech, 2012. http://pastel.archives-ouvertes.fr/pastel-00932360.
Der volle Inhalt der QuelleJourdan, Fabien. „Visualisation d'information : dessin, indices structuraux et navigation : Applications aux réseaux biologiques et aux réseaux sociaux“. Montpellier 2, 2004. http://www.theses.fr/2004MON20205.
Der volle Inhalt der QuelleDahimene, Mohammed Ryadh. „Filtrage et Recommandation sur les Réseaux Sociaux“. Electronic Thesis or Diss., Paris, CNAM, 2014. http://www.theses.fr/2014CNAM0945.
Der volle Inhalt der QuelleIn the last years, the amount of available data on the social Web has exploded. For the average user, it became hard to find quality content without being overwhelmed with publications. For service providers, the scalability of such services became a challenging task. The aim of this thesis is to achieve a better user experience by offering the filtering and recommendation features. Filtering consists to provide for a given user, the ability of receiving only a subset of the publications from the direct network. Where recommendation allows content discovery by suggesting relevant content producers on given topics. We developed MicroFilter, a scalable filtering system able to handle Web-like data flows and RecLand, a recommender system that takes advantage of the network topology as well as the content in order to provide relevant recommendations
Cossu, Jean-Valère. „Analyse de l’image de marque sur le Web 2.0“. Thesis, Avignon, 2015. http://www.theses.fr/2015AVIG0207/document.
Der volle Inhalt der QuelleAnalyse of entities representation over the Web 2.0Every day, millions of people publish their views on Web 2.0 (social networks,blogs, etc.). These comments focus on subjects as diverse as news, politics,sports scores, consumer objects, etc. The accumulation and agglomerationof these notices on an entity (be it a product, a company or a public entity) givebirth to the brand image of that entity. Internet has become in recent years aprivileged place for the emergence and dissemination of opinions and puttingWeb 2.0 at the head of observatories of opinions. The latter being a means ofaccessing the knowledge of the opinion of the world population.The image is here understood as the idea that a person or a group of peopleis that entity. This idea carries a priori on a particular subject and is onlyvalid in context for a given time. This perceived image is different from theentity initially wanted to broadcast (eg via a communication campaign). Moreover,in reality, there are several images in the end living together in parallel onthe network, each specific to a community and all evolve differently over time(imagine how would be perceived in each camp together two politicians edgesopposite). Finally, in addition to the controversy caused by the voluntary behaviorof some entities to attract attention (think of the declarations required orshocking). It also happens that the dissemination of an image beyond the frameworkthat governed the and sometimes turns against the entity (for example,« marriage for all » became « the demonstration for all »). The views expressedthen are so many clues to understand the logic of construction and evolution ofthese images. The aim is to be able to know what we are talking about and howwe talk with filigree opportunity to know who is speaking.viiIn this thesis we propose to use several simple supervised statistical automaticmethods to monitor entity’s online reputation based on textual contentsmentioning it. More precisely we look the most important contents and theirsauthors (from a reputation manager point-of-view). We introduce an optimizationprocess allowing us to enrich the data using a simulated relevance feedback(without any human involvement). We also compare content contextualizationmethod using information retrieval and automatic summarization methods.Wealso propose a reflection and a new approach to model online reputation, improveand evaluate reputation monitoring methods using Partial Least SquaresPath Modelling (PLS-PM). In designing the system, we wanted to address localand global context of the reputation. That is to say the features can explain thedecision and the correlation betweens topics and reputation. The goal of ourwork was to propose a different way to combine usual methods and featuresthat may render reputation monitoring systems more accurate than the existingones. We evaluate and compare our systems using state of the art frameworks: Imagiweb and RepLab. The performances of our proposals are comparableto the state of the art. In addition, the fact that we provide reputation modelsmake our methods even more attractive for reputation manager or scientistsfrom various fields
Raad, Eliana. „Towards better privacy preservation by detecting personal events in photos shared within online social networks“. Thesis, Dijon, 2015. http://www.theses.fr/2015DIJOS079/document.
Der volle Inhalt der QuelleToday, social networking has considerably changed why people are taking pictures all the time everywhere they go. More than 500 million photos are uploaded and shared every day, along with more than 200 hours of videos every minute. More particularly, with the ubiquity of smartphones, social network users are now taking photos of events in their lives, travels, experiences, etc. and instantly uploading them online. Such public data sharing puts at risk the users’ privacy and expose them to a surveillance that is growing at a very rapid rate. Furthermore, new techniques are used today to extract publicly shared data and combine it with other data in ways never before thought possible. However, social networks users do not realize the wealth of information gathered from image data and which could be used to track all their activities at every moment (e.g., the case of cyberstalking). Therefore, in many situations (such as politics, fraud fighting and cultural critics, etc.), it becomes extremely hard to maintain individuals’ anonymity when the authors of the published data need to remain anonymous.Thus, the aim of this work is to provide a privacy-preserving constraint (de-linkability) to bound the amount of information that can be used to re-identify individuals using online profile information. Firstly, we provide a framework able to quantify the re-identification threat and sanitize multimedia documents to be published and shared. Secondly, we propose a new approach to enrich the profile information of the individuals to protect. Therefore, we exploit personal events in the individuals’ own posts as well as those shared by their friends/contacts. Specifically, our approach is able to detect and link users’ elementary events using photos (and related metadata) shared within their online social networks. A prototype has been implemented and several experiments have been conducted in this work to validate our different contributions
Damani, Kinjal. „Les pratiques enseignantes sur les réseaux sociaux : les enseignants entre fantasmes et réalités“. Rouen, 2015. http://www.theses.fr/2015ROUEL007.
Der volle Inhalt der QuelleThe objective of this study is to understand, using a psychoanalytic clinical approach, the use or non-use of social networks like Facebook by teachers. The initial component of the study entailed the passive observation of the Facebook pages of 15 secondary and high school teachers in Europe that had been set up on their own initiative to interact with their students. To facilitate these observations, data was extracted manually from their Facebook pages over a period of seven months, from September 01, 2010 to March 31, 2011. The next component of the study consisted of 18 non-directive/unstructured interviews conducted in English or French with secondary and high school teachers. Our findings suggest that the in-between of Facebook is like a melting-pot where the teacher’s identity is constructed for some teachers and restored for others. Various types of interactions between teachers and students are described and the implications of the findings are discussed. The thesis concludes with practical recommendations for researchers and educators
Bigeard, Elise. „Détection et analyse de la non-adhérence médicamenteuse dans les réseaux sociaux“. Thesis, Lille 3, 2019. http://www.theses.fr/2019LIL3H026.
Der volle Inhalt der QuelleDrug non-compliance refers to situations where the patient does not follow instructions from medical authorities when taking medications. Such situations include taking too much (overuse) or too little (underuse) of medications, drinking contraindicated alcohol, or making a suicide attempt using medication. According to [HAYNES 2002] increasing drug compliance may have a bigger impact on public health than any other medical improvements. However non-compliance data are difficult to obtain since non-adherent patients are unlikely to report their behaviour to their healthcare providers. This is why we use data from social media to study drug non-compliance. Our study is applied to French-speaking forums.First we collect a corpus of messages written by users from medical forums. We build vocabularies of medication and disorder names such as used by patients. We use these vocabularies to index medications and disorders in the corpus. Then we use supervised learning and information retrieval methods to detect messages talking about non-compliance. With machine learning, we obtain 0.433 F-mesure, with up to 0.421 precision or 0.610 recall. With information retrieval, we reach 0.8 precision on the first ten results.After that, we study the content of the non-compliance messages. We identify various non-compliance situations and patient's motivations. We identify 3 main motivations: self-medication, seeking an effect besides the effect the medication was prescribed for, or being in addiction or habituation situation. Self-medication is an umbrella for several situations: avoiding an adverse effect, adjusting the medication's effect, underuse a medication seen as useless, taking decisions without a doctor's advice. Non-compliance can also happen thanks to errors or carelessness, without any particular motivation.Our work provides several kinds of result: annotated corpus with non-compliance messages, classifier for the detection of non-compliance messages, typology of non-compliance situations and analysis of the causes of non-compliance
Dahimene, Mohammed Ryadh. „Filtrage et Recommandation sur les Réseaux Sociaux“. Thesis, Paris, CNAM, 2014. http://www.theses.fr/2015CNAM0945/document.
Der volle Inhalt der QuelleIn the last years, the amount of available data on the social Web has exploded. For the average user, it became hard to find quality content without being overwhelmed with publications. For service providers, the scalability of such services became a challenging task. The aim of this thesis is to achieve a better user experience by offering the filtering and recommendation features. Filtering consists to provide for a given user, the ability of receiving only a subset of the publications from the direct network. Where recommendation allows content discovery by suggesting relevant content producers on given topics. We developed MicroFilter, a scalable filtering system able to handle Web-like data flows and RecLand, a recommender system that takes advantage of the network topology as well as the content in order to provide relevant recommendations
Mahabir, Laetitia-Amanda. „L'identité personnelle et les réseaux sociaux“. Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM1015.
Der volle Inhalt der QuelleThe identity of people in the digital space cannot be defined in one way. Its mode of expression is multiple. In fact, an individual can have several identities in the digital environment. It can also play different social roles according to social contexts that it faces. But what are effects of using identity masks ? The individual's identity within the social networks refers to the self-questioning, and others. The individualistic side and the community side of this identity are the foundation of the building of user's identity. Moreover, it appears that the wealth and the complexity of networks are the result of the confusion made by the law between individual and identity. In fact, the law is based on an essentialist conception of identity, by which each player has its own trajectory. But the individual does not live alone, he lives in a group and it is part of a network of social relations. The identity is made in the interaction of a claimed identity for oneself and assigned by others. Also, develop a personal identity on the fringes of the digital reality is to distinguish the person of the concept of online presence which is eminently declarative and performative.All this leads to reconsider the place of identity in the digital space. To understand the question of the construction of personal identity in social network, different approaches will be detailed. Those approaches are aimed to ensure everyone an identity according his wishes. Also, it will be necessary to adapt the existing measures to the virtual reality, in order to establish a more secure regime of personal identity, in respect of the rights of each user's personnality
Veny, Yoann. „Socio-Sémantique du Web Politique: Une Analyse de l’Espace de Compétition Thématique et Topographique Entre Communautés Politiques Belges Francophones“. Doctoral thesis, Universite Libre de Bruxelles, 2017. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/261521.
Der volle Inhalt der QuelleDoctorat en Sciences politiques et sociales
info:eu-repo/semantics/nonPublished
Maigrot, Cédric. „Détection de fausses informations dans les réseaux sociaux“. Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1S085.
Der volle Inhalt der QuelleFalse information are multiplying and are spreading quickly on social networks. In this thesis, we analyze the publications from a multimodal point of view between the text and the associated image. Several studies were conducted during this thesis. The first compares several types of media present on social networks and aims to discriminate them automatically. The second one allows the detection and the localization of modifications in an image thanks to the comparison with an old version of this image. Finally, we focused on merged knowledge based on the predictions of other research teams to create a single system
Nana, jipmo Coriane. „Intégration du web social dans les systèmes de recommandation“. Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLC082/document.
Der volle Inhalt der QuelleThe social Web grows more and more and gives through the web, access to a wide variety of resources, like sharing sites such as del.icio.us, exchange messages as Twitter, or social networks with the professional purpose such as LinkedIn, or more generally for social purposes, such as Facebook and LiveJournal. The same individual can be registered and active on different social networks (potentially having different purposes), in which it publishes various information, which are constantly growing, such as its name, locality, communities, various activities. The information (textual), given the international dimension of the Web, is inherently multilingual and intrinsically ambiguous, since it is published in natural language in a free vocabulary by individuals from different origin. They are also important, specially for applications seeking to know their users in order to better understand their needs, activities and interests. The objective of our research is to exploit using essentially the Wikpédia encyclopedia, the textual resources extracted from the different social networks of the same individual in order to construct his characterizing profile, which can be exploited in particular by applications seeking to understand their users, such as recommendation systems. In particular, we conducted a study to characterize the personality traits of users. Many experiments, analyzes and evaluations were carried out on real data collected from different social networks
Stella, Elie. „L’adaptation du droit pénal aux réseaux sociaux en ligne“. Thesis, Université de Lorraine, 2019. http://www.theses.fr/2019LORR0344.
Der volle Inhalt der QuelleOnline social networks demonstrate the transcription, as well as the intensification, of human relationships on a digital level. More generally, the apparition and widespread use of these sites reveal a profound evolution of social relationships that began in the mid-2000s. Consequently, criminal law, as a “mirror of civilisation” has necessarily been impacted to the extent of warranting its adaptation.These websites undeniably constitute a new legal arena within which delinquent online behaviour is present. For the most part, online social networks are merely a new medium for infringements, to which pre-existing criminal offences are perfectly designed to apply, should they arise. However, new forms of infringements have emerged from these places of exchange, highlighting the structural shortcomings within criminal law, that manifest as the inability of pre-existing criminal offences to cover these new forms of infringements. Criminal law has therefore adapted through the creation of new criminal offences, demonstrating the profound evolution of the protection of privacy, identity and more generally, private life, under criminal law.Social networks also raise criminal law issues with regard to the suppression of delinquent online behaviour that can be found on them. In this case, the regimes of criminal responsibility applicable to different social network players, users and operators, demonstrate a certain unsuitability which manifests itself as the ineffectiveness of criminal law on social networks. The solution therefore consists of developing, or rather diversifying the response to emerging offences and providing a framework for the regulation of content in collaboration with the administrative authorities. A new regime of responsibility thus emerges, applicable to the main digital sharing platforms, that progressively promotes a principle of compliance within them. Ultimately, criminal law adapts to online social networks as much as social networks adapt to criminal law
Junier, Aurore. „Analyse de performance et de stabilité des réseaux de télécommunication“. Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2013. http://tel.archives-ouvertes.fr/tel-00932176.
Der volle Inhalt der QuelleRamrajsingh, Athissingh. „Les nouvelles technologies Web, facteur d'un glissement de la prérogative politique? : approche critico-discursive du mode d'existence idéologique du Web 2.0 révélant ses impensés et analyse des enjeux sur le plan macro-sociétal“. Aix-Marseille 3, 2009. http://www.theses.fr/2009AIX32079.
Der volle Inhalt der QuelleThe concept of “Web 2. 0” has been so much discussed since it was first introduced in September 2005, that it has become difficult to perceive all its technical, economic and political developments. This work proposes a critical approach to this concept with a view to revealing its full scope, which seems to be hidden, either consciously or unconsciously, by technical experts as well as political or economic actors. The first part of this research work is based upon the discursive analysis of a compendium of bloggers’ postings in order to characterise the way “Web 2. 0” is viewed by bloggers. Two major arguments support this representation, namely increasing participation to the creation of content and power seizure by Internet surfers. The second part puts both arguments to the test by studying the workings of a given community, then the “success” of “Web 2. 0” through what is referred to as “simultaneity paradox” by physicists. Lastly, this work proposes a political insight into “web 2. 0” by putting it back into perspective and by shedding light on the manner in which it is giving rise to a shift in prerogative from politicians to private actors in the Internet industry
Tackx, Raphaël. „Analyse de la structure communautaire des réseaux bipartis“. Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS550.pdf.
Der volle Inhalt der QuelleIn the real world, numerous networks appear naturally, they are everywhere, in many disciplines, for example in computer science with router networks, satellite networks, webpage networks, in biology with neural networks, in ecology with biological interaction networks, in linguistic with synonym networks, in law with legal decision networks, in economy with interbank networks, in social sciences and humanities with social networks. Generally, a network reflects the interactions between many entities of a system. These interactions have different sources, a social link or a friendship link in a social network, a cable in a router network, a chemical reaction in a protein-protein interaction network, a hyperlink in a webpage network. Furthermore, the rapid democratization of digital technology in our societies, with internet in particular, leads to create new systems which can be seen as networks. Finally, all these networks depict very specific features : they come from pratical contexts, most of the time they are big (they may be comprised of several billion of nodes and links, containing a large amount of information), they share statistical properties. In this regard, they are called real-world networks or complex networks. Nowaday, network science is a research area in its own right focusing on describing and modeling these networks in order to reveal their main features and improve our understanding of their mecanisms. Most of the works in this area use graphs formalism which provides a set of mathematical tools well suited for analyzing the topology of these networks. It exists many applications, for instance applications in spread of epidemy or computer viruses, weakness of networks in case of a breakdown, attack resilience, study for link prediction, recommandation, etc. One of the major issue is the identification of community structure. The large majority of real-world networks depicts several levels of organization in their structure. Because of there is a weak global density coupled with a strong local density, we observe that nodes are usually organized into groups, called communities, which are more internally connected than they are to the rest of the network. Moreover, these structures have a meaning in the network itself, for example communities of a social network may correspond to social groups (friends, families, etc.), communities of a protein-protein network may translate fonctions of a cell, communities may be also related to similar subjects in a webpage network [...]
Diaby, Mamadou. „Méthodes pour la recommandation d’offres d’emploi dans les réseaux sociaux“. Thesis, Sorbonne Paris Cité, 2015. http://www.theses.fr/2015USPCD012/document.
Der volle Inhalt der QuelleWe are entering a new era of data mining in which the main challenge is the storing andprocessing of massive data : this is leading to a new promising research and industry field called Big data. Data are currently a new raw material coveted by businesses of all sizes and all sectors. They allow organizations to analyze, understand, model and explain phenomen a such as the behavior of their users or customers. Some companies like Google, Facebook,LinkedIn and Twitter are using user data to determine their preferences in order to make targeted advertisements to increase their revenues.This thesis has been carried out in collaboration between the laboratory L2TI andWork4, a French-American startup that offers Facebook recruitment solutions. Its main objective was the development of systems recommending relevant jobs to social network users ; the developed systems have been used to advertise job positions on social networks. After studying the literature about recommender systems, information retrieval, data mining and machine learning, we modeled social users using data they posted on their profiles, those of their social relationships together with the bag-of-words and ontology-based models. We measure the interests of users for jobs using both heuristics and models based on machine learning. The development of efficient job recommender systems involved to tackle the problem of categorization and summarization of user profiles and job descriptions. After developing job recommender systems on social networks, we developed a set of systems called Work4 Oracle that predict the audience (number of clicks) of job advertisements posted on Facebook, LinkedIn or Twitter. The analysis of the results of Work4 Oracle allows us to find and quantify factors impacting the popularity of job ads posted on social networks, these results have been compared to those of the literature of Human Resource Management. All our proposed systems deal with privacy preservation by only using the data that social network users explicitly allowed to access to ; they also deal with noisy and missing data of social network users and have been validated on real-world data provided by Work4
Renaud, Clément. „Conception d'un outil d'analyse et de visualisation des mèmes internet : le cas du réseau social chinois Sina Weibo“. Electronic Thesis or Diss., Paris, ENST, 2014. http://www.theses.fr/2014ENST0070.
Der volle Inhalt der QuelleWe develop a data mining and visualisation toolkit to study how the information is shared on online social network services. This software allows to observe relationships between conversational, semantical, temporal and geographical dimensions of online communication acts. Internet memes are short messages that spread quickly through the Web. Following models that remain largely unknown, they articulate personal discussions, societal debates and large communication campaign. We analyse a set of Internet memes by using methods from social network analysis and Chinese natural language processing on a large corpus of 200 million tweets which represents/reflects the overall activity on the Chinese social network Sina Weibo in 2012. An interactive visualisation interface showing networks of words, user exchanges and their projections on geographical maps provides a detailed understanding of actual and textual aspects of each meme spread. An analysis of hashtags in the corpus shows that the main content from Sina Weibo is largely similar to the ones in traditional media (advertisement, entertainment, etc.). Therefore, we decided to not consider hashtags as memes representatives, being mostly byproducts of wellplanned strategic or marketingcampaigns. Our final approach studies a dozen of memes selected for the diversity of their topic: humor, political scandal, breaking news and marketing
Caillaut, Gaëtan. „Apprentissage d'espaces prétopologiques pour l'extraction de connaissances structurées“. Electronic Thesis or Diss., Orléans, 2019. http://www.theses.fr/2019ORLE3208.
Der volle Inhalt der QuellePretopology is a mathematical theory whose goal is to relax the set of axioms governing the well known topology theory. Weakening the set of axioms mainly consists in redefining the pseudo-closure operator which is idempotent in topology. The non-idempotence of the pretopological pseudo-closure operator offers an appropriate framework for the modeling of various phenomena, such as iterative processes evolving throughout time. Pretopology is the outcome of the generalisation of several concepts, amongst topology but also graph theory. This thesis is divided in four main parts. The first one is an introduction to the theoretical framework of the pretopology, as well as an overview of several applications in domains where the pretopology theory shines, such as machine learning, image processing or complex systems analysis.The second part will settle the logical modeling of pretopological spaces which allows to define pretopological spaces by a logical and multi-criteria combination. This modeling enables learning algorithms to define pretopological spaces by learning a logical formula. This part will also present an unrestricted pretopological spaces learning algorithm. Unrestricted pretopological spaces can be quite hard to manipulate, especially when the studied population has some structural properties that can be described in a more restricted space. This is why the third part is dedicated to the automatic learning of pretopological spaces of type V. These spaces are defined by a set of prefilters which impose a particular structure. The LPSMI algorithm, which is the main contribution of this work, is presented in this part. This algorithm relies on the multi-instance learning principles to accurately capture the structural properties of pretopological spaces of type V. Finally, the last part consists of multiple applications of the theoretical framework presented in this thesis. Applications to lexical taxonomies extraction, community detection and extraction of temporal relations, as part of a NLP process, will be presented in order to show the usefulness, the relevance and the flexibility of pretopological spaces learning
Agosto, Franco Layda J. „Optimisation d'un réseau social d'échange d'information par recommendation de mise en relation“. Chambéry, 2005. http://www.theses.fr/2005CHAMS051.
Der volle Inhalt der QuelleToday, the World Wide Web is getting essential while surfing for information. Surfers have different information needs. Thanks to results from social network analysis and many other experiences observed from existing recommender systems, we have concluded that a tendency is to prefer information having certain approval : "asking to a friend" means to point out the person having a good level of knowledge about the information needed. As others before us, we have also verified that in many information exchange systems (as mailing groups) only few people produce actively information but a lot of them take it. Can we really modify this strong tendency? Try to answer to this question is the principal objective of our work. To do it in a positive way, we have imagined a way to influence user's motivation to exchange information. For that, we use regulation mechanisms that are intended to promote a dynamic information exchange, to allow users to control their personal information (thanks to bookmarks) and to exhibit a social awareness. This is why we have proposed some recommender algorithms. They exploit the network topology formed of relations between persons exchanging information and the information that they handle. Our approach is then supported by a collaborative web system named SoMeONe (Social Media using Opinions through a trust Network). We think that the most important contribution is our idea of recommending contacts instead of information. For that, we want to validate the efficiency of information flow in the social exchange network. We have then proposed some postulates, principles and hypothesis to validate our approach. The hypothesis take in count the users' objectives (information needed) , and for that some quality criterias have been developed in order to also validate the system's objectives (optimize the social network structure). To raise those objectives we have introduced some social indicators (which are our algorithms) that we named SocialRank
Raad, Elie. „Découverte des relations dans les réseaux sociaux“. Phd thesis, Université de Bourgogne, 2011. http://tel.archives-ouvertes.fr/tel-00702269.
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