Abstract: In this paper we present a simple and easy to use tool that can be used for content analytics of Twitter tweets. The tool was developed primarily for researchers with minimal computing background who wish to visually analyze tweets text and the associated metadata (screen names, hashtags, mention, etc.) across a timeline or a user-specified timeline. The tool is open source and built on top of the R programming platform, R-Shiny and R-wordcloud. The tool uses a word cloud approach to visualize both the metadata and the n-gram sequences that make up the tweets collection (the tweet corpus). A filter mechanism of the tool allows the researcher to control the type and amount of data displayed in the associated word clouds – allowing for a finer resolution of analysis.
Keywords: n-grams, Natural Language Processing, R & R-Shiny, Twitter Data, Visual Text Analytics, word cloud
Download this article: JISAR - V10 N1 Page 15.pdf
Recommended Citation: Jafar, M. J., Waldman, M. (2017). An Interactive Toolbox for Twitter Content Analytics. Journal of Information Systems Applied Research, 10(1) pp 15-28. http://jisar.org/2017-10/ ISSN: 1946-1836. (A preliminary version appears in The Proceedings of CONISAR 2016)