Suchergebnisse

12th Turkish National Software Engineering Symposium, UYMS 2018; Istanbul; Turkey; 10 September 2018 through 12 September 2018 ; Digital data represent our daily activities and tendencies. One of its main source is Online Social Networks (OSN) such as Facebook, YouTube etc. OSN are generating continuously high volume of data and define a dynamic virtual environment. This environment is mostly represented by graphs. Analysis of OSN data (i.e.,extracting any kind of relations and tendencies) defines valuable information for economic, socio-cultural and politic decisions. Community detection is important to analyze and understand underlying structure and tendencies of OSNs. When this information can be analysed successfully, software engineering tools and decision support systems can produce more successful results for end users. In this study, we present a survey of selected outstanding modularity-based static community detection algorithms and do comparative analysis among them in terms of modularity, running time and accuracy. We use different real-world OSN test beds selected from SNAP dataset collection such as Facebook Ego network, Facebook Pages network (Facebook gemsec), LiveJournal, Orkut and YouTube networks.

Keeping in touch -- Social media history -- Facebook -- Instant messaging and microblogging -- Sharing snaps -- Connecting to social media -- How information spreads -- The business of social media -- Signing up and starting out -- Keeping it private -- Smart, safe social media -- Social media issues -- Cyberbullying -- Glossary -- Further resources -- Index

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. © 2014 SAGE Publications.

"Donath presents new approaches to creating interfaces for social interaction. She addresses such topics as visualizing social landscapes, conversations, and networks; depicting identity with knowledge markers and interaction history; delineating public and private space; and bringing the online world' s open sociability into the physical world. Donath asks fundamental questions about how we want to live online and offers thought-provoking design that explore radically new ways of interacting and communicating."--

Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models

Presents latest research on applications of optimization and scheduling in sports management Provides an overview of the state of the art in scientific models for addressing complex challenges in sports management and sports administration Presents recent results from studies into the arising field of social networks and their impact on sports.

As technology changes, so too have its applications and our uses and experiences with them have changed as well. The emergence of new technologies offer opportunities for new ways of interacting, playing, working and learning. It is within the context of simultaneous excitement and anxiety that we discuss Virtual Social Networks

This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edited work will appeal to researchers, practitioners and students interested in the latest developments of social network analysis.