Abstract: With nearly 2 billion users worldwide, Facebook is the most popular social media site in the world. Despite this popularity and ubiquity, it has been lightly studied in the literature. Our manuscript examines the most popular Facebook sites (pages) in the United States dealing with society and performs a comprehensive linguistics and sentiment analysis on these sites. Using Azure machine learning for sentiment and LIWC (Linguistic Inquiry and Word Count) for linguistics, our review finds significant similarities and differences in posts on Facebook pages that have the most fans (most popular). Implications and opportunities for further research are presented.
Keywords: Sentiment analysis, Facebook, Linguistic analysis, LIWC
Download this article: JISAR - V11 N1 Page 23.pdf
Recommended Citation: Peslak, A. (2018). Facebook Fanatics: A Linguistic and Sentiment Analysis of the Most “Fanned” Facebook Pages. Journal of Information Systems Applied Research, 11(1) pp 23-33. http://jisar.org/2018-11/ ISSN: 1946-1836. (A preliminary version appears in The Proceedings of CONISAR 2017)