Suchergebnisse

Today, 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. ; De nos jours, les réseaux sociaux ont considérablement changé la façon dont les ...

Today, 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. ; De nos jours, les réseaux sociaux ont considérablement changé la façon dont les ...

Today, 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. ; De nos jours, les réseaux sociaux ont considérablement changé la façon dont les ...

Online social networks are increasing in popularity. Among teens, they are fast becoming synonymous with being online, i.e., using the Internet (Lenhart et al., 2011). As online social networks became widespread, it is found that people are using it for various purposes including work, leisure, entertainment, as well as healthcare. In this paper, the authors share their viewpoint and insights on the use of online social networks for healthcare related purposes which are sometimes also referred to as Health 2.0, or as Health Social Networks (HSNs). The authors examine the potential of HSNs in empowering patients and health information seekers towards wellbeing and healthy living. They also discuss the various potential uses of HSNs by healthcare providers and healthcare organizations. A three-dimensional framework is developed by analyzing 37 best-known commercial HSN sites to help categorize HSNs that can aide in their design process. More importantly, we provide an in-depth discussion on the future role of social networks within Healthcare.

Social media communication is characterized by reduced anonymity and off-to-online social interactions. These characteristics require scholars to revisit social influence mechanisms online. The current study builds on social influence literature to explore social network and gender effects on online behavior. Findings from a quasi-experiment suggest that both network-related variables and gender are significantly associated with online behavior. Perceived social environment, measured by personal network exposure rate, is more significant than objective reality, measured by frequency of received social messages, in determining behavior. We discuss the implications of social contagion effects on web-based strategic communication—including advertising, political campaigns, and social mobilization. Data limitations and the difficulty of measuring social network influence via social media are also discussed.

Why investigate online talk? : Introducing the research design framework -- What are we looking for? : Identifying the object of interest in online talk -- What does online talk represent? : Philosophical assumptions and methodological alignment -- What is the research question and how can we answer it? : Up from data, down from design -- When should online talk be treated as data? : ethical practices -- How will the data be acquired? : Characterizing, bounding, and extracting online talk as a data source -- (with Robyn Singleton) how will the data be analyzed? : Part one: Quantitative approaches including content analysis, statistical modeling, and computational methods -- How will the data be analyzed? : Part two: Qualitative approaches including thematic, narrative, conversation, and discourse analysis -- Have we found what we were looking for? : Revisiting the research design framework.

"Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present the latest advances of various topics in intelligent-social-networks and illustrates how organizations can gain competitive advantages by applying the different emergent techniques in real-world scenarios. The work incorporates experience reports, survey articles, and intelligence techniques and theories with specific network technology problems. Topics and Features: Provides an overview social network tools, and explores methods for discovering key players in social networks, designing self-organizing search systems, and clustering blog sites, surveys techniques for exploratory analysis and text mining of social networks, approaches to tracking online community interaction, and examines how the topological features of a system affects the flow of information, reviews the models of network evolution, covering scientific co-citation networks, nature-inspired frameworks, latent social networks in e-Learning systems, and compound communities, examines the relationship between the intent of web pages, their architecture and the communities who take part in their usage and creation, discusses team selection based on members' social context, presents social network applications, including music recommendation and face recognition in photographs, explores the use of social networks in web services that focus on the discovery stage in the life cycle of these web services. This useful and comprehensive volume will be indispensible to senior undergraduate and postgraduate students taking courses in Social Intelligence, as well as to researchers, developers, and postgraduates interested in intelligent-social-networks research and related areas"--Publisher's description

Die Studie untersucht - gleichsam zwischen 'Schrift und Bild' - die Spezifika von Sozialität innerhalb von Social Network Sites. Der Komplexität dieser Forschungsfrage wird durch eine Forschungskonzeption entsprochen, die Diskurse der Selbstthematisierung, der sozialen Aushandlungsprozesse und der Medienumgebung reziprok betrachtet. Das Forschungsdesign basiert auf der Grounded Theory und verbindet somit sukzessiv und iterativ sowohl theoretische als auch qualitativ empirische Perspektiven auf Sozialität. Daraus resultiert eine detaillierte Beschreibung der Sozialität in Social Network Sites, die darüber hinaus die Konstruktion des sozialen Raums und die Relevanz sozialer Kontinuität diskutiert.