Sentiment analysis for Twitter during U.S. Presidential Election2020 Using the big data framework

Document Type : Original Article

Author

* Assistant Professor of Journalism and Communication Technology, Department of Mass Communication, Faculty of Arts, Minia University.

Abstract

The study aimed to Sentiment analysis for Twitter during the US presidential elections 2020, in order to identify the positive and negative feelings of the tweets according to the Biden and Trump hashtags via the Twitter platform using the Big Data framework, and to reveal the negative and positive feelings of the tweets of users in swing states and their loyalty to the candidates, and the reliability of the Twitter platform, As a hypothetical opinion poll that can predict the results of the voting share in the US presidential elections 2020, and to identify the pivotal issues that dominated tweets during this period, the study reached many results, the most important of which are: Both candidates for the elections obtained similar results in both positive and negative opinions with different Less than 1% in the sentiment rating in favor of Biden, than we expect him to win Joe Biden with a higher positive sentiment than Trump, which was later verified by the actual results of the US elections 2020, where the actual results showed Biden's victory and with these results, It can be concluded that sentiment analysis using Twitter data can be an accurate and low method We also found that campaign coverage, election integrity, the impact of coronavirus, and Supreme Court appointments were the top four issues that surfaced on Twitter during this election.

Keywords

Files

Share

How to cite

Statistics