Journal
2017 IEEE 29TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2017)
Volume -, Issue -, Pages 760-764Publisher
IEEE
DOI: 10.1109/ICTAI.2017.00120
Keywords
Twitter; Sentiment Analysis; Opinion Mining; Machine learning; Classification; Emotions; Politics; GOP Debate
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Twitter plays a vital role in spreading information and influencing people's opinions in a specific direction. As an easy-to-use platform, Twitter motivates people to share their thoughts and express their opinions. It has been shown by researchers that tracking and analyzing public opinions from social media can help to predict certain political events. This has attracted the attention of politicians towards extracting public opinions regarding their strategies. Consequently, the sentiment analysis of political tweets becomes more valued over time. This study examines Twitter discussions about then-US Republican presidential candidate Donald Trump after his primary debates. It further investigates people's emotions regarding Trump after his debates to see if we can detect whether the tweets support or oppose the candidate. One of the key findings of this study is recognizing that negative or positive polarities in the tweets is not a good indicator to determine support for this candidate.
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