1.

Record Nr.

UNINA9910298995103321

Titolo

Online Social Media Analysis and Visualization [[electronic resource] /] / edited by Jalal Kawash

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014

ISBN

3-319-13590-2

Edizione

[1st ed. 2014.]

Descrizione fisica

1 online resource (243 p.)

Collana

Lecture Notes in Social Networks, , 2190-5428

Disciplina

004

006.312

519.5

621

Soggetti

Application software

Statistics 

Physics

Data mining

Computer Appl. in Social and Behavioral Sciences

Statistics for Social Sciences, Humanities, Law

Applications of Graph Theory and Complex Networks

Data Mining and Knowledge Discovery

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Identifying Event-Specific Sources from Social Media -- Demographic and Psychographic Estimation of Twitter Users Using Social Structures -- Say It with Colors: Language-Independent Gender Classification on Twitter -- TUCAN: Twitter User Centric Analyzer -- Evaluating Important Factors and Effective Models for Twitter Trend Prediction -- Rings: a Visualization Mechanism to Enhance the User Awareness on Social Networks -- Friends and Circles – A Design Study for Contact Management in Egocentric Online Social Networks -- Genetically Optimized Realistic Social Network Topology Inspired by Facebook -- A Workbench for Visual Design of Executable and Re-usable Network Analysis Workflows -- On the Usage of Network Visualization for Multiagent System Verification.



Sommario/riassunto

This edited volume addresses the vast challenges of adapting Online Social Media (OSM) to developing research methods and applications. The topics cover generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, behavior detection, mining social content for common trends, identifying and ranking social content sources, building friend-comprehension tools, and many others. Each of the ten chapters tackle one or more of these issues by proposing new analysis methods or new visualization techniques, or both, for famous OSM applications such as Twitter and Facebook. This collection of contributed chapters address these challenges. Online Social Media has become part of the daily lives of hundreds of millions of users generating an immense amount of 'social content'. Addressing the challenges that stem from this wide adaptation of OSM is what makes this book a valuable contribution to the field of social networks.