Sudarmin, - (2021) Analysis of twitter sentiment in COVID-19 era using fuzzy logic method. Journal of Soft Computing Exploration (JOSCEX), 2 (1). pp. 1-5. ISSN 2746-0991

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Abstract

The sentiment is an assessment of attitudes towards certain events or things. Collecting opinion is known as a sentiment from existing data. This technique can also help analyze the opinions given by people in assessing certain objects. The best available source for gathering sentiment is the internet. In the era of the Covid-19 pandemic, many people access social media, especially Twitter to give their opinion on certain objects. Twitter is known as the social media that is accessed by users to post their opinions online. By using soft computing, especially fuzzy logic, it is possible to design, create and build bots that can analyze user opinions on Twitter. This model is used for data sentiment analysis on Twitter. The results showed that the sentiment analysis during the Covid-19 period was still dominant with positive tweets. As many as 48% of tweets are positive, 30% are negative tweets and 22% are neutral tweets. The use of applications to identify tweet sentiment during Covid-19 uses a combination of fuzzy logic methods with artificial intelligence. With the help of the Twitter API, you can get tweet data during the Covid-19 pandemic so you can find out the frequently used tweet sentiments.

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