Dissertations / Theses on the topic 'Online social networks'
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Vallapu, Sai Krishna. "Towards Network False Identity Detection in Online Social Networks." Thesis, Southern Illinois University at Edwardsville, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10246101.
Full textIn this research, we focus on identifying false identities in social networks. We performed a detailed study on different string matching techniques to identify user profiles with real or fake identity. In this thesis, we focus on a specific case study on sex offenders. Sex offenders are not supposed to be online on social networking sites in few states. To identify the existence of offenders in social networks, we ran experiments to compare datasets downloaded from Facebook and offender registries. To identify the most suitable string matching technique to solve this particular problem, we performed experiments on various methods and utilized the most appropriate technique, the Jaro-Winkler algorithm. The major contribution of our research is a weight based scoring function that is capable of identifying user records with full or partial data revealed in social networks. Based on our data samples created using metadata information of Facebook, we were able to identify the sex offender profiles with real identity and seventy percent of the sex offenders with partial information.
Rahman, Mahmudur. "Data Verifications for Online Social Networks." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/2299.
Full textWebberley, William. "Inferring interestingness in online social networks." Thesis, Cardiff University, 2014. http://orca.cf.ac.uk/68758/.
Full textBaatarjav, Enkh-Amgalan. "Privacy Management for Online Social Networks." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc283816/.
Full textCox, Shirley A. "Online social network member attitude toward online advertising formats /." Online version of thesis, 2010. http://hdl.handle.net/1850/11588.
Full textAlim, Sophia. "Vulnerability in online social network profiles : a framework for measuring consequences of information disclosure in online social networks." Thesis, University of Bradford, 2011. http://hdl.handle.net/10454/5507.
Full textSáez-Trumper, Diego. "Finding relevant people in online social networks." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/283658.
Full textL'objectiu d'aquesta tesi és desenvolupar noves tècniques per trobar persones rellevants en les Xarxes Socials a Internet. Així doncs, considerem diferents nocions de rellevància, tenint en compte el punt de vista dels prove ïdors del servei (com Facebook) i dels anunciants, però també de persones que intenten proposar noves idees i temes a la xarxa. La nostra investigació va més enllà de la popularitat de les persones, mostra que els usuaris amb molts seguidors no són necessàriament els més rellevants. Específicament, desenvolupem tres algorismes que permeten: (i) calcular el valor (monetari) que cada usuari produeix per al prove ïdor del servei; (ii) trobar usuaris que proposen noves idees i creen tendències; i (iii) un sistema de recomanació que permet als anunciants (centrant-nos en botigues locals, com ara un restaurant o un pub) trobar clients potencials. Addicionalment, lliurem informació útil sobre el comportament dels usuaris segons la seva rellevància i popularitat, mostrant, entre altres coses, que els usuaris més actius solen ser més rellevants que els populars. A més a més, mostrem que normalment els usuaris molt populars arriben tard a les noves tendències, mentre que usuaris de menor popularitat, però molt actius, generen valor i fomenten noves idees a la xarxa .
El objetivo de esta tesis es desarrollar nuevas técnicas para encontrar personas relevantes en las Redes Sociales en Internet. Para ello, consideramos diferentes nociones de relevancia, tomando el punto de vista de los proveedores del servicio (como Facebook) y de los anunciantes, pero también de las personas que intentan proponer nuevas ideas y temas en la red. Nuestra investigación va más allá de la popularidad de las personas, mostrando que los usuarios con muchos seguidores no son necesariamente los más relevantes. Espeficamente, desarollamos tres algoritmos que permiten: (i) calcular el valor (monetario) que cada usuario produce para el proveedor del servicio; (ii) encontrar usuarios que proponen nuevas ideas y crean tendencias; y (iii) un sistema de recomendación que permite a los anunciantes (centrándonos en tiendas locales, tales como un restaurant o un pub) encontrar potenciales clientes. Adicionalmente, proporcionamos información útil sobre el comportamiento de los usuarios según su relevancia y popularidad, mostrando - entre otras cosas - que los usuarios más activos suelen ser más relevantes que los populares. Más aún, mostramos que normalmente los usuarios muy populares llegan tarde a las nuevas tendencias, y que existen usuarios menos populares, pero muy activos que generan valor y fomentan nuevas ideas en la red.
Recalde, Lorena. "Modeling users preferences in online social networks." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/663756.
Full textEl objetivo de esta tesis es desarrollar nuevos y diversos métodos para modelar las preferencias de los usuarios en las Redes Sociales Online. Los métodos propuestos tienen como finalidad ser aplicados en áreas de investigación como la Personalización o Recomendación de ítems y la Detección de Grupos de Usuarios con gustos similares. Dichos métodos pueden ser agrupados en dos tipos: i) métodos basados en técnicas de análisis de texto (Parte I, Capítulos del 3 al 5) y ii) métodos basados en teoría de grafos (Parte II, Capítulos 6 y 7). Con los métodos planteados en la Parte I es posible determinar el nivel de interés de los usuarios en temas que son compartidos en plataformas de microblogging. Hemos tomado como caso de estudio la participación digital de tweeters en la política. Los métodos propuestos en la Parte II buscan definir un rol para los usuarios en Redes Sociales, ya sea como creadores o generadores de contenido y distribuidores o consumidores de contenido. Hemos planteado un método donde usuarios con intereses similares pero con distinto rol, son agrupados en una misma comunidad de forma que nuevo contenido se propague más rápidamente.
The objective of this thesis is to develop new and diverse methods to model the preferences of the users in the Online Social Networks. The proposed methods are intended to be applied in areas of research such as Personalization or Recommendation of items and the detection of groups of users with similar tastes. These methods can be grouped into two types: i) methods based on text analysis techniques (Chapters 3 to 5) and ii) methods based on graph theory (Chapters 6 and 7). With the methods proposed in i) it is possible to determine the level of interest of users on topics that are shared on microblogging platforms. We have taken as a case study the digital participation of tweeters in politics. The methods proposed in ii) seek to define a role for users in social networks, whether as creators or content generators and distributors or content consumers. We have proposed a method where users with similar interests but with different roles, are grouped in the same community so that new content spreads more quickly.
Bhardwaj, Shally. "Personality Assessment Using Multiple Online Social Networks." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31734.
Full textAhmad, Waqar, and Asim Riaz. "Predicting Friendship Levels in Online Social Networks." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3351.
Full textLewis, Makayla. "Cerebral palsy, online social networks and change." Thesis, City University London, 2013. http://openaccess.city.ac.uk/3011/.
Full textYang, Yile, and 楊頤樂. "Noncooperative information diffusion in online social networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206693.
Full textpublished_or_final_version
Electrical and Electronic Engineering
Doctoral
Doctor of Philosophy
Marks, Christopher E. (Christopher Edward). "Analytic search methods in online social networks." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112012.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 175-185).
This thesis presents and evaluates methods for searching and analyzing social media data in order to improve situational awareness. We begin by proposing a method for network vertex search that looks for the target vertex by sequentially examining the neighbors of a set of "known" vertices. Using a dynamic programming approach, we show that there is always an optimal "block" search policy, in which all of the neighbors of a known vertex are examined before moving on to another vertex. We provide a precise characterization of the optimal policy in two specific cases: (1) when the connections between the known vertices and the target vertex are independent, and (2) when the target vertex is connected to at most one known vertex. We then apply this result to the problem of finding new accounts belonging to Twitter users whose previous accounts had been suspended for extremist activity, quantifying the performance of our optimal search policy in this application against other policies. In this application we use thousands of Twitter accounts related to the Islamic State in Iraq and Syria (ISIS) to develop a behavioral models for these extremist users. These models are used to identify new extremist accounts, identify pairs of accounts belonging to the same user, and predict to whom a user will connect when opening an account. We use this final model to inform our network search application. Finally, we develop a more general application of network search and classification that obtains a set of social media users from a specified location or group. We propose an expand -- classify methodology which recursively collects users that have social network connections to users inside the target location, and then classifies all of the users by maximizing the probability over a factor graph model. This factor graph model accounts for the implications of both observed user profile features and social network connections in inferring location. Using geo-located data to evaluate our method, we find that our classification method typically outperforms Twitter's native search methods in building a dataset of Twitter users in a specific location.
by Christopher E. Marks.
Ph. D.
Laraqui, Jawad. "Activity based interfaces in online social networks." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41658.
Full textIncludes bibliographical references (p. 51).
The goal of the project is to explore how activity-based interfaces can create more meaningful experiences for the users and builders of online social networking sites. Medina, a social-networking site based on the idea of exchanging knowledge, explores new interfaces for visualizing connections between people and ideas. The site constantly measures interactions between people and their interests in order to create a more accurate picture of what relationships and information are important.
by Jawad Laraqui.
M.Eng.
Xu, Hailu. "Efficient Spam Detection across Online Social Networks." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470416658.
Full textHong, Dan. "Sharing private data in online social networks /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?CSED%202009%20HONG.
Full textFidalgo, Patrícia Seferlis Pereira. "Learning networks and moodle use in online courses: a social network analysis study." Doctoral thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8862.
Full textThis research presents a case study on the interactions between the participants of the forums of four online undergraduate courses from the perspective of social network analysis (SNA). Due to lack of studies on social networks in online learning environments in higher education in Portugal we have choose a qualitative structural analysis to address this phenomenon. The context of this work was given by the new experiences in distance education (DE) that many institutions have been making. Those experiences are a function of the changes in educational paradigms and due to a wider adoption of Information and Communication Technologies (ICT) from schools as well as to the competitive market. Among the technologies adopted by universities are the Learning Management Systems (LMSs) that allow recording, storing and using large amounts of relational data about their users and that can be accessed through Webtracking. We have used this information to construct matrices that allowed the SNA. In order to deepen knowledge about the four online courses we were studying we have also collect data with questionnaires and interviews and we did a content analysis to the participations in the forums. The three main sources of data collection led us to three types of analysis: SNA, statistical analysis and content analysis. These types of analysis allowed, in turn, a three-dimensional study on the use of the LMS: 1) the relational dimension through the study of forums networks and patterns of interaction among participants in those networks, 2) the dimension relative to the process of teaching and learning through content analysis of the interviews; 3) and finally the dimension related to the participants' perceptions about the use of LMS for educational purposes and as a platform for creating social networks through the analysis of questionnaires.With the results obtained we carried out a comparative study between the four courses and tried to present a reflection on the Online Project of the University as well as possible causes that led to what was observed. We have finished with a proposal of a framework for studying the relational aspects of online learning networks aimed at possible future research in this area.
Chiu, Wei-Yi. "The analysis of social capital in online social communities." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/46995/1/Wei-Yi_Chiu_Thesis.pdf.
Full textLei, Siyu, and 雷思宇. "Online influence maximization." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/210187.
Full textpublished_or_final_version
Computer Science
Master
Master of Philosophy
Noe, Nyala. "Personality homophily and social-spatial characteristics in online social networks." Thesis, Cardiff University, 2018. http://orca.cf.ac.uk/118510/.
Full textMusial, Katarzyna. "Recommendation system for online social network." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4105.
Full textIkhalia, Ehinome. "A malware threat avoidance model for online social network users." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/16039.
Full textIrani, Danesh. "Preventing abuse of online communities." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44895.
Full textMakinde, Oghenefejiro Winnie. "Assessing the credibility of online social network messages." Thesis, University of Derby, 2018. http://hdl.handle.net/10545/622367.
Full textPérez-Solà, Cristina. "Towards understanding privacy risks in online social networks." Doctoral thesis, Universitat Autònoma de Barcelona, 2016. http://hdl.handle.net/10803/386415.
Full textOnline Social Networks (OSNs) are now one of the most popular services on the Internet. When these lines were written, there were four OSN sites in the Alexa's top ten global ranking and the most used OSNs were having hundreds of millions of daily active users. People use OSNs to share all kinds of contents: from personal attributes (like names, age, or gender), to location data, photos, or comments. Moreover, OSNs are characterized by allowing its users to explictly form relationships (e.g. friendship). Additionally, OSNs include not only information the users conscientiously post about themselves, but also information that is generated from the interaction of users in the platform. Both the number of users and the volume of data shared make privacy in OSNs critical. This thesis is focused on studying privacy related to OSNs in two different contexts: crawling and learning. First, we study the relation between OSN crawling and privacy, a topic that so far received limited attention. We find this scenario interesting because it is affordable for even a low-budget attacker. Second, we study how to extract information from the relationships OSN users form. We then expand our findings to other graph-modeled problems.
Alzamzami, Fatimah. "Towards Multimedia-Based Storytelling in Online Social Networks." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32521.
Full textAloufi, Samah. "Trust-aware Link Prediction in Online Social Networks." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23303.
Full textKershaw, Daniel. "Language change and evolution in Online Social Networks." Thesis, Lancaster University, 2018. http://eprints.lancs.ac.uk/129787/.
Full textBotha, Leendert W. "Modeling online social networks using Quasi-clique communities." Thesis, Stellenbosch : Stellenbosch University, 2011. http://hdl.handle.net/10019.1/17859.
Full textENGLISH ABSTRACT: With billions of current internet users interacting through social networks, the need has arisen to analyze the structure of these networks. Many authors have proposed random graph models for social networks in an attempt to understand and reproduce the dynamics that govern social network development. This thesis proposes a random graph model that generates social networks using a community-based approach, in which users’ affiliations to communities are explicitly modeled and then translated into a social network. Our approach explicitly models the tendency of communities to overlap, and also proposes a method for determining the probability of two users being connected based on their levels of commitment to the communities they both belong to. Previous community-based models do not incorporate community overlap, and assume mutual members of any community are automatically connected. We provide a method for fitting our model to real-world social networks and demonstrate the effectiveness of our approach in reproducing real-world social network characteristics by investigating its fit on two data sets of current online social networks. The results verify that our proposed model is promising: it is the first community-based model that can accurately reproduce a variety of important social network characteristics, namely average separation, clustering, degree distribution, transitivity and network densification, simultaneously.
AFRIKAANSE OPSOMMING: Met biljoene huidige internet-gebruikers wat deesdae met behulp van aanlyn sosiale netwerke kommunikeer, het die analise van hierdie netwerke in die navorsingsgemeenskap toegeneem. Navorsers het al verskeie toevalsgrafiekmodelle vir sosiale netwerke voorgestel in ’n poging om die dinamika van die ontwikkeling van dié netwerke beter te verstaan en te dupliseer. In hierdie tesis word ’n nuwe toevalsgrafiekmodel vir sosiale netwerke voorgestel wat ’n gemeenskapsgebaseerde benadering volg, deurdat gebruikers se verbintenisse aan gemeenskappe eksplisiet gemodelleer word, en dié gemeenskapsmodel dan in ’n sosiale netwerk omskep word. Ons metode modelleer uitdruklik die geneigdheid van gemeenskappe om te oorvleuel, en verskaf ’n metode waardeur die waarskynlikheid van vriendskap tussen twee gebruikers bepaal kan word, op grond van hulle toewyding aan hulle wedersydse gemeenskappe. Vorige modelle inkorporeer nie gemeenskapsoorvleueling nie, en aanvaar ook dat alle lede van dieselfde gemeenskap vriende sal wees. Ons verskaf ’n metode om ons model se parameters te pas op sosiale netwerk datastelle en vertoon die vermoë van ons model om eienskappe van sosiale netwerke te dupliseer. Die resultate van ons model lyk belowend: dit is die eerste gemeenskapsgebaseerde model wat gelyktydig ’n belangrike verskeidenheid van sosiale netwerk eienskappe, naamlik gemiddelde skeidingsafstand, samedromming, graadverdeling, transitiwiteit en netwerksverdigting, akkuraat kan weerspieël.
Othman, Salem. "Autonomous Priority Based Routing for Online Social Networks." Kent State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=kent1526481500145998.
Full textZhen, Yufeng. "A NOVEL SPAM CAMPAIGN IN ONLINE SOCIAL NETWORKS." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3290.
Full textWei, Wei. "Improving Security and Privacy in Online Social Networks." W&M ScholarWorks, 2013. https://scholarworks.wm.edu/etd/1539623628.
Full textColetto, Mauro. "Analysis of Polarized Communities in Online Social Networks." Thesis, IMT Alti Studi Lucca, 2017. http://e-theses.imtlucca.it/204/1/Coletto_phdthesis.pdf.
Full textVandersluis, Kelly S. "Creating social action through Facebook." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3008.
Full textVita: p. 61. Thesis director: Byron Hawk. Submitted in partial fulfillment of the requirements for the degree of Master of Arts in English. Title from PDF t.p. (viewed July 2, 2008). Includes bibliographical references (p. 54-60). Also issued in print.
Shaikh, Sajid S. "Computations in social network." [Kent, Ohio] : Kent State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=kent1185560088.
Full textKong, Chenguang, and 孔臣光. "Collaborative streaming in mobile social networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47849897.
Full textpublished_or_final_version
Computer Science
Master
Master of Philosophy
Mega, Giuliano. "On Social Overlays and Their Application to Decentralized Online Social Networks." Doctoral thesis, Università degli studi di Trento, 2013. https://hdl.handle.net/11572/367684.
Full textMega, Giuliano. "On Social Overlays and Their Application to Decentralized Online Social Networks." Doctoral thesis, University of Trento, 2013. http://eprints-phd.biblio.unitn.it/999/1/thesis.pdf.
Full textSmith, Matthew Scott. "Social Capital in Online Communities." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2730.
Full textGreschbach, Benjamin. "Privacy Issues in Decentralized Online Social Networks and other Decentralized Systems." Doctoral thesis, KTH, Teoretisk datalogi, TCS, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-196118.
Full textPopulära sociala nätverkstjänster som Facebook och Instagram bygger på en logiskt centraliserad systemarkitektur. Tjänsteleverantörerna har därför tillgång till omfattande ansamlingar av känsliga personuppgifter,vilket innebär en oundviklig risk för integritetskränkningar. Med jämna mellanrum läcks dessa informationsansamlingar till tredje part – antingen när tjänsteleverantören själv säljer eller ger dem tillexterna aktörer, eller när obehöriga får åtkomst till tjänsteleverantörens datasystem. Decentraliserade sociala nätverkstjänster (eng. Decentralized Online Social Networks, DOSNs) är en lovande utveckling för att minska denna risk och för att skydda användarnas personliga information såväl från tjänsteleverantören som från tredje part. Ett vanligt sätt att implementera ett DOSN är genom en icke-hierarkisk nätverksarkitektur (eng. peer-to-peer network) för att undvika att känsliga personuppgifter samlas på ett ställe som är under tjänsteleverantörens kontroll. Kryptering används för att skydda kommunikationen och för att realisera åtkomstkontrollen av information som ska delas med andra användare. Att inte längre ha en tjänsteleverantör som har tillgång till all data innebär att den största riskfaktorn for integritetskränkningar tas bort. Men genom att ersätta den centrala tjänsteleverantören med ett decentraliserat system tar vi även bort ett visst integritetsskydd. Integritetsskyddet var en konsekvens av att förmedlingen av all användarkommunikation skedde genom tjänsteleverantörens servrar. När ansvaret för lagring av innehållet, hantering av behörigheterna, åtkomst och andra administrativa uppgifter övergår till användarna själva, blir det en utmaning att skydda metadata för objekt och informationsflöden, även om innehållet är krypterat. I ett centraliserat system är dessa metadata faktiskt skyddade av tjänsteleverantören – avsiktligt eller som en sidoeffekt. För att implementera de olika funktioner som ska finnas i ett integritetsskyddande DOSN, är det nödvändigt både att lösa dessa generella utmaningar och att hantera frånvaron av en betrodd tjänsteleverantör som har full tillgång till all data. Användarautentiseringen borde till exempel ha samma användbarhet som i centraliserade system. Det vill säga att det är lätt att ändra lösenordet, upphäva rättigheterna för en stulen klientenhet eller återställa ett glömt lösenord med hjälp av e-post eller säkerhetsfrågor – allt utan att förlita sig på en betrodd tredje part. Ett annat exempel är funktionen att kunna söka efter andra användare. Utmaningen där är att skydda användarinformationen samtidigt som det måste vara möjligt att hitta användare baserad på just denna informationen. En implementation av en sådan funktion i ett DOSN måste klara sig utan en betrodd tjänsteleverantör som med tillgång till alla användardata kan upprätthålla ett globalt sökindex. I den här avhandlingen analyserar vi de generella risker för integritetskränkningar som finns i DOSN, särskilt de som orsakas av metadata. Därutöver föreslår vi tre integritetsskyddande implementationer av vanliga funktioner i en social nätverkstjänst: lösenordsbaserad användarautentisering, en användarsökfunktion med en kunskapströskel och en inbjudningsfunktion för evenemang med detaljerade sekretessinställningar. Alla tre implementationerna är lämpliga för DOSN-scenarier eftersom de klarar sig helt utan en betrodd, central tjänsteleverantör, och kan därför även användas i andra sammanhang såsom icke-hierarkiska nätverk eller andra system som måste klara sig utan en betrodd tredje part. Slutligen analyserar vi en attack på ett specifikt decentraliserat system, anonymitetstjänsten Tor, och diskuterar hur systemet kan skyddas mot de analyserade sårbarheterna.
QC 20161115
Libardi, Paula Luciene Oliveira 1980. "Detecção computacional de falecidos em redes sociais online." [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/267725.
Full textDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Tecnologia
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Resumo: A identificação de usuários falecidos em Redes Sociais Online é um desafio em aberto e, dado o tamanho das principais redes, abordagens que envolvam intervenção manual são impraticáveis. Usuários inativos por longo tempo inviabilizam soluções simples tais como a expiração de um prazo desde o último acesso, o que torna difícil a diferenciação entre inativos e falecidos. Esta pesquisa iniciou-se com o pressuposto de que o problema poderia ser parcialmente resolvido com métodos automáticos e a hipótese era de que dois métodos aqui propostos, um baseado na análise de frequência de mensagens trocadas entre usuários e outro fundamentado na combinação de informações da topologia da rede junto a inspeções de mensagens, poderiam identificar satisfatoriamente parte dos usuários falecidos. Para testar esta hipótese, recorreu-se à simulação computacional, usando topologias livre de escala e aleatória. O programa que simula as redes foi construído de forma a aplicar e testar os métodos de identificação de falecidos, seguindo padrões de projeto que permitem facilmente a troca ou o encadeamento dos algoritmos a validar. Dessa característica, originou-se um terceiro método, que é a combinação das saídas de algoritmos detectores aplicados anteriormente à rede. Os resultados da pesquisa validaram a hipótese, sendo que os dois métodos propostos inicialmente tiveram, cada qual, índices de acerto superiores a 70% na maioria dos casos simulados, independentemente da topologia da rede. Em ambos os métodos, no entanto, é necessária uma calibração de dois parâmetros operacionais, o que exige algum conhecimento da rede examinada e influencia na taxa de detecção. O último método mostrou-se bastante eficiente, com detecção correta superior a 94%, e capaz de absorver flutuações na taxa de detecção dos demais métodos advindas de suas respectivas parametrizações. Portanto, os objetivos da pesquisa foram plenamente atingidos, com a validação da hipótese inicial, a proposta de três métodos para a solução do problema e a geração de um produto tecnológico, o Demortuos, que é o software de simulação da rede e teste dos métodos, atualmente em processo de registro no Instituto Nacional da Propriedade Industrial (INPI). Adicionalmente, foram abertas possibilidades para o desenvolvimento de métodos automáticos para busca de outras classes de usuários
Abstract: Identifying deceased users in Online Social Networks is an open challenge and, given the size of the main networks, approaches involving manual intervention are impractical. Inactive users for a long time prevent simple solutions such as the expiration of a period since the last entry, making it difficult to differentiate between inactive and deceased users. This research began with the assumption that the problem could be partially solved with automated methods and the hypothesis was that two methods proposed here, one based on frequency analysis of messages exchanged between users and the other based on the combination of topology information network with the messages of inspections, could satisfactorily identify the part of deceased users. To test this hypothesis, we used the computer simulation, using free topologies of scale and random, the latter for comparison purposes. The program that simulates the network was constructed to implement and test the deceased identification methods, following design patterns that easily allow the exchange or the chain of algorithms to validate. This characteristic gave up a third method, which is combining the outputs of detectors algorithms previously applied to the network. The survey results validated the hypothesis, and the two proposed methods initially had, each, hit rates of over 70% in most cases simulated, regardless of the network topology. In both methods, however, two operating parameters calibration is necessary, which requires some knowledge of the network and examined influences the detection rate. The last method proved to be very efficient with proper detection above 94%, and able to absorb fluctuations in the detection rate of other methods resulting from their respective parameterization. Therefore, the research objectives were fully achieved, with the validation of the initial hypothesis, the proposed three methods for the solution of the problem and the generation of a technological product, Demortuos, which is the network simulation software and testing methods currently in the registration process at the National Institute of Industrial Property (INPI). Moreover, possibilities are opened for the development of automated methods to search for other classes of users
Mestrado
Tecnologia e Inovação
Mestra em Tecnologia
Niu, Guolin, and 牛国林. "Temporal modeling of information diffusion in online social networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206478.
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Electrical and Electronic Engineering
Doctoral
Doctor of Philosophy
Greschbach, Benjamin. "Privacy Analysis and Protocols for Decentralized Online Social Networks." Licentiate thesis, KTH, Teoretisk datalogi, TCS, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-165377.
Full textI dagens populära sociala nätverkstjänster, såsom Facebook, Google+ och Twitter, finns en risk för integritetskränkningar. Risken är en oundviklig konsekvens av den logiskt centraliserade struktur som dessa tjänster bygger på. Decentraliserade sociala nätverkstjänster (eng. Decentralized Online Social Networks, DOSNs) är en lovande utveckling för att minska risken och skydda användarnas personliga information från tjänsteleverantören och dem som leverantören samarbetar med. Ett vanligt sätt att implementera ett DOSN är genom en icke-hierarkisk nätverksarkitektur (eng. peer-to-peer network) för att undvika att känsliga personuppgifter ansamlas på ett ställe under tjäns televerantörens kontroll. Att inte längre ha en tjänsteleverantör som har tillgång till alla data tar bort den största risken för integritetskränkningar. Men genom att ersätta den centrala tjänsteleverantören med ett decentraliserat system tar vi även bort visst integritetsskydd. Integritetsskyddet var en konsekvens av att förmedlingen av all användarkommunikation skedde genom tjänsteleverantörens mellanservrar. När ansvaret för lagring av innehållet, hantering av behörigheterna, åtkomst och andra administrativa uppgifter övergår till användarna själva, då blir det en utmaning att skydda metadata för objekten och informationsflöden, även om innehållet är krypterat. I ett centraliserat system är dessa metadata faktiskt skyddade av tjänsteleverantören - avsiktligt eller som en sidoeffekt. För att implementera de olika funktioner som ska finnas i ett integritetsskyddande DOSN, är det nödvändigt att både lösa dessa generella utmaningar och att hantera frånvaron av ett betrodd tredjepart som har full tillgång till all data. Autentiseringen av användarna, till exempel, borde ha samma användbarhet som finns i centraliserade system. Det vill säga att det är lätt att ändra lösenordet, dra tillbaka rättigheterna för en stulen klientenhet, eller återställa ett glömt lösenord med hjälp av e-post eller säkerhetsfrågor - allt utan att förlita sig på en betrodd tredjepart. Ett annat exempel är funktionen att kunna söka efter andra användare. Utmaningen där är att skydda informationen om användarna samtidigt som det måste vara möjligt att hitta användare baserad på samma information. En implementation av denna funktion i ett DOSN måste klara sig utan en betrodd tjänsteleverantör som med tillgång till alla användares data kan upprätthålla ett globalt sökindex. I den här avhandlingen analyserar vi de generella risker för integritetskränkningar i DOSN, särskilt de som orsakas av metadata. Dessutom föreslår vi två integritetskyddande implementationer av vanliga funktioner i en socialt nätverkstjänst: lösenordbaserad användarautentisering och en användarsökfunktionen med en kunskaptröskel. Båda implementationerna är lämpliga för DOSN-scenarier eftersom de klarar sig helt utan en betrodd, central tjänstleverantör, och kan därför också användas i andra sammanhang: såsom icke-hierarkiska nätverk eller andra system som måste klara sig utan en betrodd tredjepart.
QC 20150428
Kayes, Md Imrul. "Content Abuse and Privacy Concerns in Online Social Networks." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5967.
Full textKamal, Noreen. "Designing online social networks to motivate health behaviour change." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45242.
Full textTarbzouni, Abdulrahman I. "SocialRank : ranking users and information in online social networks." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53167.
Full textIncludes bibliographical references (leaf 39).
The goal of this project is to explore the design and implementation of SocialRank. SocialRank is a personalized ranking algorithm that provides--for each user--ratings for people in his online social network. Subsequently, these ratings are used to rank incoming information received by the user from those in his social network. We analyze the use of actions on online social networks as proxies for measuring the strength of relationships between users and introduce an action scoring mechanism that uses different factors to evaluate an action's significance. We implement SocialRank in a generic online social network that we build as part of this research project and explore the effectiveness and usefulness of SocialRank.
by Abdulrahman I. Tarbzouni.
M.Eng.
Chaabane, Abdelberi. "Online Social Networks : Is it the end of Privacy ?" Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM017/document.
Full textSharing information between users constitutes the cornerstone of the Web 2.0. Online Social Networks (OSN), with their billions of users, are a core component of this new generation of the web. In fact, OSNs offer innovative services allowing users to share their self-generated content (e.g., status, photos etc.) for free. However, this free access is usually synonymous with a subtle counterpart: the collection and usage of users' personal information in targeted advertisement. To achieve this goal, OSN providers are collecting a tremendous amount of personal, and usually sensitive, information about their users. This raises concerns as this data can be exploited by several entities to breach user privacy. The primary research goals of this thesis are directed toward understanding the privacy impact of OSNs.Our first contribution consists in demonstrating the privacy threats behind releasing personal information publicly. Two attacks are constructed to show that a malicious attacker (i.e., any external attacker with access to the public profile) can breach user privacy and even threaten his online security.Our first attack shows how seemingly harmless interests (e.g., music interests) can leak privacy-sensitive information about users. In particular, we infer their undisclosed (private) attributes using the public attributes of other users sharing similar interests. Leveraging semantic knowledge from Wikipedia and a statistical learning method, we demonstrated through experiments ---based on more than 104K Facebook profiles--- that our inference technique efficiently predicts attributes that are very often hidden by users.Our second attack is at the intersection of computer security and privacy. In fact, we show the disastrous consequence of privacy breach on security by exploiting user personal information ---gathered from his public profile--- to improve the password cracking process.First, we propose a Markov chain password cracker and show through extensive experiments that it outperforms all probabilistic password crackers we compared against. In a second step, we systematically analyze the idea that additional personal information about a user helps in speeding up password guessing. We propose a methodology that exploits this information in the cracking process and demonstrate that the gain can go up to 30%.These studies clearly indicate that publicly disclosing personal information harms privacy, which calls for a method to estimate this loss. Our second contribution tries to answer this question by providing a quantitative measure of privacy. We propose a practical, yet formally proved, method to estimate the uniqueness of each profile by studying the amount of information carried by public profile attributes. To achieve our goal, we leverage Ads Audience Estimation platform and an unbiased sample of more than 400K Facebook public profiles. Our measurement results show that the combination of gender, current city and age can identify close to 55% of users to within a group of 20 and uniquely identify around 18% of them.In the second part of this thesis, we investigate the privacy threats resulting from the interactions between the OSN platform and external entities. First, we explore the tracking capabilities of the three major OSNs (i.e., Facebook, Google+ and Twitter) and show that ``share-buttons'' enable them to persistently and accurately track users' web activity. Our findings indicate that OSN tracking is diffused among almost all website categories which allows OSNs to reconstruct a significant portion of users' web profile and browsing history.Finally, we develop a measurement platform to study the interaction between OSN applications --- of Facebook and RenRen --- and fourth parties. We show that several third party applications are leaking user information to ``fourth'' party entities such as trackers and advertisers. This behavior affects both Facebook and RenRen with varying severity
Monk, Adam Joel. "The Diffusion of New Music through Online Social Networks." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1337902485.
Full textAlbalawi, Rania. "Toward a Real-Time Recommendation for Online Social Networks." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42255.
Full textAgostinelli, Sara. "Impacts of student identity construction in online social networks." Pullman, Wash. : Washington State University, 2009. http://www.dissertations.wsu.edu/Thesis/Summer2009/s_agostinelli_061809.pdf.
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