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SocMedDataExtractionContentAnalysis 2016 : Social Media Data Extraction and Content Analysis


When Jan 1, 2000 - Jan 31, 2016
Where N/A
Submission Deadline TBD
Final Version Due Jan 31, 2016

Call For Papers

Call for Chapters
Proposals Submission Deadline: September 30, 2015
Full Chapters Due: October 30, 2015

This book collects research on the datafication of social media platforms, from the Web to specific social media platforms: social networking sites, content-sharing sites, microblogging sites, email systems, and others. This book will include chapters on related data extraction / visualization / analysis technologies, data extraction methods, analytical techniques, and unique cases. Ultimately, this text will capture insights about the datafying of social media.

In the age of the Social Web, much of the world has gone online as individuals and groups to use sociality to amplify every aspect of human life: work, family, sport, art, politics, governance, and other facets. These online interactions have left trails of data—direct text and multimedia contents; metadata (titles, labels, descriptive text, and tags); user profiles and user interrelationships; and other data that may be extracted and analyzed for other ways of knowing. The Surface Web itself enables learning about http networks, collected snippets of information, geolocational information, and technological site understructures. Online text corpuses may be analyzed with natural language analytical programs for text summarization, content networks, text searches for contextual analysis (and word trees). The information from microblogging sites enable real-time analysis of content streams and real-time event-graphing. Tags used on digital images and digital videos may be analyzed for relatedness to other tags. Article networks may be mapped on wikis to understand topical relatedness; this same feature may be used also to profile the human (and ‘bot) editors on open- and crowd-sourced encyclopedias. Video networks may be extracted to understand the types of video contents created around particular topics. Further, user network accounts (on video sharing sites) may be profiled and analyzed in a social network context. Social networking sites based around socializing or work or other targeted interests may also be plumbed for social networks and interchanged messages (message streams). There are numerous ways in which the Web and social media may be harnessed for awareness and decision-making.

Datafying social media is about extracting empirical information from the Web and social media platforms, conducting various queries and data visualizations on the contents, and emerging with fresh insights that inform awareness and decision-making.

Social Media Data Extraction and Content Analysis will address various social media platforms, available technologies employed to extract and analyze data, application analytical techniques, and ultimately what is knowable from the various platforms.

Target Audience
The target audience for this book will be scholars, researchers, professionals, and in-field practitioners engaged in social media and its myriad uses for learning, awareness, and decision-making.

Recommended Topics

The Surface Web

The Deep (Hidden) Web

The Dark Web

Social Media Platforms
Social networking sites
Content sharing sites
Learning Objects
Microblogging sites
Blogging sites
Wiki sites
Social tagging
Basic electronic communications (email)

Methods and Technologies for Data Extraction
Tools for content analysis
Tools for content network analysis
Tools for de-aliasing identities, ego and entity analysis
Site scraping

Content Analysis of Messaging

Content Analysis of Multimedia

Exploiting Metadata

Online Egos and Entities on Social Media Platforms

Identifying Non-Obvious and Latent Egos and Entities
Bots, sensors

Mapping Online Events, Extended Eventgraphing

Mapping Online Conversations

Real-Time Sentiment Analysis of Messaging

Cross-Cultural Explorations in the Social Web

Creating Content Networks

Cases, and others

Submission Procedure
All are invited to submit a chapter proposal of 500 words explaining the proposed chapter before September 30, 2015. Full chapters, 10,000-12,000 words each, are expected to be submitted by October 30, 2015. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project. Chapters with multiple authors are welcome, even encouraged.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Social Media Data Extraction and Content Analysis. All manuscripts are accepted based on a double-blind peer review editorial process.

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the “Information Science Reference” (formerly Idea Group Reference), “Medical Information Science Reference,” “Business Science Reference,” and “Engineering Science Reference” imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit This publication is anticipated to be released in 2016.

Book Series

For release in the Advances in Data Mining & Database Management (ADMDM) series

Series Editor(s): David Taniar (Monash University, Australia)

ISSN: 2327-1981
The Advances in Data Mining & Database Management (ADMDM) series aims to bring together research in information retrieval, data analysis, data warehousing, and related areas in order to become an ideal resource for those working and studying in these fields. IT professionals, software engineers, academicians and upper-level students will find titles within the ADMDM book series particularly useful for staying up-to-date on emerging research, theories, and applications in the fields of data mining and database management.

Editorial Advisory Board

Dr. Marc A. Smith, Director, Social Media Research Foundation

Nancy Hays, EDUCAUSE

Dr. Duygu Mutlu Bayraktar, Istanbul University, Turkey

Important Dates
Chapter Proposal Submission:September 30, 2015

Full chapter Submission: October 30, 2015

Review Results to Authors: November 20, 2015

Revised Chapter Submission: December 15, 2015

Dr. Shalin Hai-Jew
Kansas State University

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