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Analysis of Tweets on 2016 US Presidential Election Candidates
| Content Provider | Semantic Scholar |
|---|---|
| Author | Hu, Gongzhu Kodali, Snehitha Padamati, Anusha |
| Copyright Year | 2016 |
| Abstract | Sentiment analysis is a process that focuses on the understanding of the opinions or emotions from text messages. It has been applied to many areas, from product reviews for online marketing to people’s opinions for political events. In this paper, we present a sentiment analysis of text messages extracted from the social media Twitter about the candidates of the 2016 US Presidential Election. The objective of this paper is to find how the traditional method for sentiment analysis compares to the polls and if the sentiment measures can be used as an indicator to predict who will win the election. The statistics software system R with its sentiment tool was used in our analysis. We found that Donald Trump has been leading in the sentiment measures up to the present time, immediately after the two parties’ national conventions. It appears contradicting to the recent pools that show Hilary Clinton is ahead. However, the trend in the sentiment showed Clinton is on the rise. keywords: Sentiment analysis, Sentiment measures, tweet, 2016 US presidential election |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://people.cst.cmich.edu/hu1g/caine2016paper.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
