Social media usage in academic research

Recently researchers have used “conversation prism” and “social media prisma”, to consolidate social medias with respect to their use. Although both identified 25 types, having average five examples each, they did not identify contribution of each type in academic research. Moreover some of mentioned social services had been suspended or changed. In this paper we attempt to access each social media mentioned in conversation prism in order to first, identify services that are operational to date, services which have suspended and those which have changed during course of time. Second, we compare number of publications associated with each social media, in order to identify which social media has contributed most to academic research. Third, we attempt to find correlation between number of publications and development tools provided by respective social applications. Fourth, social medias are ranked with respect to number of times other social medias share content with respective social application. It was found that out of 168 social applications, 10% changed their service objective while 13% were suspended. Among all social application, AMAZON had highest i.e. 147,000 number of citations on Google scholar whereas 90.7% of total citations were contributed by top 30 social medias. For developers, 22 out of top 30 social medias provided developer options in form of either application programming interface (API) or software development kits (SDK) and Facebook was found to be most cross referred social media based on content sharing. Finally conclusion and future work of study is presented.

[1]  Victoria L. Crittenden,et al.  We're all connected: The power of the social media ecosystem , 2011 .

[2]  Rosa M. Carro,et al.  Sentiment analysis in Facebook and its application to e-learning , 2014, Comput. Hum. Behav..

[3]  Bo Li,et al.  Scaling social media applications into geo-distributed clouds , 2012, 2012 Proceedings IEEE INFOCOM.

[4]  Stéphane Gançarski,et al.  Web page segmentation evaluation , 2015, SAC.

[5]  Lei Zhang,et al.  A Survey of Opinion Mining and Sentiment Analysis , 2012, Mining Text Data.

[6]  A. Kaplan,et al.  Users of the world, unite! The challenges and opportunities of Social Media , 2010 .

[7]  Sandra Duhé,et al.  An overview of new media research in public relations journals from 1981 to 2014 , 2015 .

[8]  Maria da Conceição F. Santiago,et al.  Immigrant Women’s Perspective on Prenatal and Postpartum Care: Systematic Review , 2015, Journal of Immigrant and Minority Health.

[9]  Yinyuan Liu Chinesische Social Media im Überblick , 2016 .

[10]  Sebastian K. Boell,et al.  Debating systematic literature reviews (SLR) and their ramifications for IS: a rejoinder to Mike Chiasson, Briony Oates, Ulrike Schultze, and Richard Watson , 2015, J. Inf. Technol..

[11]  Matthew A. Russell,et al.  Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More , 2018 .

[12]  Tim O'Reilly,et al.  What is Web 2.0: Design Patterns and Business Models for the Next Generation of Software , 2007 .

[13]  Carson Kai-Sang Leung,et al.  Interactive discovery of influential friends from social networks , 2014, Social Network Analysis and Mining.

[14]  Graham Vickery,et al.  Participative Web And User-Created Content: Web 2.0 Wikis and Social Networking , 2007 .

[15]  Anahid Bassiri,et al.  Challenges of Location-Based Services Market Analysis: Current Market Description , 2014, LBS.

[16]  Daniel Lewis,et al.  What is web 2.0? , 2006, CROS.

[17]  Eric W. T. Ngai,et al.  Social media models, technologies, and applications: An academic review and case study , 2015, Ind. Manag. Data Syst..