Feat: A Facebook Extraction And Analysis Toolkit

ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
Haihoua Yang (Creator)
Appalachian State University (ASU )
Web Site: https://library.appstate.edu/
Cindy Norris

Abstract: Social media usage has become mainstream. According to a recent study done by Edison Research in 2016, 78% of the U.S. population has a social media profile [8]. The number of active Facebook users is over one billion. In addition, 71% of adults use Facebook, which is the target of this thesis. Because Facebook is so widely used, it is also a popular medium for those wanting to promote their products and ideas, including presidential candidates. Many researchers have extracted data from social media sites, including Facebook, to predict the outcome of elections, to predict election turnout by political party, and to determine voter opinions. This thesis will discuss the development and use of a suite of tools for gathering and analyzing data collected from the social media site, Facebook. Although the suite of tools can be used to collect data from any public Facebook site, this thesis will specifically focus on using the tools to extract data from the pages of presidential candidates. In addition to extracting Facebook data and storing the data in a database, tools in the suite can be used to analyze and visualize the collected data.

Additional Information

Yang, H. (2016). "Feat: A Facebook Extraction And Analysis Toolkit." Unpublished Master's Thesis. Appalachian State University, Boone, NC.
Language: English
Date: 2016
Text analysis, Facebook, social media, sentiment analysis, word frequency

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