Littérature scientifique sur le sujet « Réseaux sociaux (Internet) – Analyse informatique »
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Articles de revues sur le sujet "Réseaux sociaux (Internet) – Analyse informatique"
Bousquet, C. « Veille sanitaire sur internet et sur les réseaux sociaux–recherche et analyse des effets indésirables médicamenteux rapportés par les patients dans les réseaux sociaux ». Toxicologie Analytique et Clinique 26, no 4 (décembre 2014) : 214–15. http://dx.doi.org/10.1016/j.toxac.2014.09.013.
Texte intégralBocher, R., et M. Grohens. « PSYGÉ - Le patient et son psychiatre : relations médecins-malades en 2030 ». European Psychiatry 29, S3 (novembre 2014) : 638. http://dx.doi.org/10.1016/j.eurpsy.2014.09.158.
Texte intégralNapieralski, Andrzej Jr, et Alina Goniewicz. « La rupture du tabou sur internet –analyse linguistique des mèmes sur Aleksander Kwaśniewski ». ACTA UNIVERSITATIS LODZIENSIS. FOLIA LITTERARIA ROMANICA, no 12 (22 mai 2017) : 191–204. http://dx.doi.org/10.18778/1505-9065.12.17.
Texte intégralRoumieux, Olivier. « Internet et réseaux sociaux. Dossier / réalisé par Dominique Cardon, Paris : La Documentation française, 2011. – 135 p., Problèmes politiques et sociaux , mai 2011, n° 984 : 9,90 €. Le Réseau social d’entreprise. Alain Garnier, Guy Hervier, Paris : Hermès Science Publications : Lavoisier, 2011. – 255 p. – (Management et informatique). – ISBN 978-2-7462-2984-6 : 59 € ». Documentaliste-Sciences de l'Information Vol. 48, no 4 (1 décembre 2011) : VIII. http://dx.doi.org/10.3917/docsi.484.0070h.
Texte intégralGajanigo, Paulo Rodrigues, et Rogério Ferreira de Souza. « MANIFESTAÇÕES SOCIAIS E NOVAS MÍDIAS : a construção de uma cultura contra-hegemônica ». Caderno CRH 27, no 72 (19 juin 2015). http://dx.doi.org/10.9771/ccrh.v27i72.19431.
Texte intégralGagnon, Éric. « Sociologie et anthropologie ». Anthropen, 2016. http://dx.doi.org/10.17184/eac.anthropen.038.
Texte intégralThèses sur le sujet "Réseaux sociaux (Internet) – Analyse informatique"
Mezghani, Manel. « Analyse des réseaux sociaux : vers une adaptation de la navigation sociale ». Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30127/document.
Texte intégralThe 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.
Texte intégralOur 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.
Texte intégralFluctuating 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.
Texte intégralIn 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.
Texte intégralOnline 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.
Texte intégralFluctuating 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.
Texte intégralNowadays, 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/.
Texte intégralIn 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.
Texte intégralSince 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.
Texte intégralThe 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
Livres sur le sujet "Réseaux sociaux (Internet) – Analyse informatique"
Analyzing and securing social networks. Boca Raton : Taylor & Francis Group, 2016.
Trouver le texte intégralLes liaisons numériques : Vers une nouvelle sociabilité ? Paris : Éd. du Seuil, 2010.
Trouver le texte intégralCyberspaces of everyday life. Minneapolis, MN : University of Minnesota Press, 2005.
Trouver le texte intégral1962-, Ma Jianhua, dir. Mobile social networking and computing : A multidisciplinary integrated perspective. Boca Raton : CRC Press, Taylor & Francis Group, 2015.
Trouver le texte intégralLa souveraineté numérique. Paris : Stock, 2014.
Trouver le texte intégralOntario. Esquisse de cours 12e année : Changements et défis sociaux hsb4m cours préuniversitaire. Vanier, Ont : CFORP, 2002.
Trouver le texte intégralMcCumber, John. Assessing and managing security risk in IT systems : A structured methodology. Boca Raton, FL : Auerbach Publications, 2005.
Trouver le texte intégralOntario. Esquisse de cours 12e année : Le Canada et le monde : une analyse géographique cgw4u cours préuniversitaire. Vanier, Ont : CFORP, 2002.
Trouver le texte intégralThe social net : Understanding our online behavior. Oxford : Oxford University Press, 2013.
Trouver le texte intégralYair, Amichai-Hamburger, dir. The social net : Understanding human behavior in cyberspace. Oxford : Oxford University Press, 2005.
Trouver le texte intégralChapitres de livres sur le sujet "Réseaux sociaux (Internet) – Analyse informatique"
BONNAIRE, Anne-Coralie. « L’épidémie au prisme des réseaux sociaux numériques ». Dans Les épidémies au prisme des SHS, 35–44. Editions des archives contemporaines, 2022. http://dx.doi.org/10.17184/eac.5988.
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