Sentiment analysis on predicting presidential election: Twitter used case
Source of Publication
Communications in Computer and Information Science
© Springer Nature Switzerland AG 2020. Twitter is a popular tool for social interaction over the Internet. It allows users to share/post opinions, social media events, and interact with other political and ordinary people. According to Statista web site 2019 statistical report, it estimated that the number of users on Twitter had grown dramatically over the past couple of years to research 300 million users. Twitter has become the largest source of news and postings for key presidents and political figures. Referring to the Trackalytics 2019 report, the recent president of the USA had posted 4,000 tweets per year, which indicates an average of 11–12 tweets per day. Our research proposes a technique that extracts and analyzes tweets from blogs and predicts election results based on tweets analysis. It assessed the people’s opinion and studied the impact that might predict the final results for the Turkey 2018 presidential election candidates. The final results were compared with the actual election results and had a high accuracy prediction percentage based on the collected 22,000 tweets.
Data mining, Election, Negative polarity, Positive polarity, Sentiment analysis, Tweets, Twitter API, Virtualization
Baker Al Barghuthi, Nedaa and E. Said, Huwida, "Sentiment analysis on predicting presidential election: Twitter used case" (2020). All Works. 3070.
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