Title

Using Twitter Sentiment Analysis to Analyze Self-Sentiment of the POTUS

Document Type

Conference Proceeding

Publication Date

2018

Publication Title

2018 Proceedings of the Conference on Information Systems Applied Research

ISSN

2167-1508

Abstract

This article provides a discussion of different tools that can be used to perform research on Twitter. The study then utilizes sentiment analysis to demonstrate self-sentiment of the POTUS and compare it with popular news sources. A comparison in 2 time periods and 4 months apart was made to determine if there is a change in the self-sentiment of the POTUS versus common news sources. To perform sentiment analysis, we utilize Python and the Vader and Pandas libraries, and statistical analysis was performed for each of the datasets. The first round of tests were based on a November dataset and revealed the means between the public, FOX, CNN and the President were not equal and that the POTUS had a higher self-sentiment than the sentiment of the news sources. The second round of tests were based on the following April data collection and revealed that the self-sentiment of the POTUS was not significantly different from the public or FOX. However, it was significantly different from CNN indicating a possible clash between the POTUS and CNN news.

Comments

©2018 ISCAP (Information Systems & Computing Academic Professionals)

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