Does it make you sad? A lexicon-based sentiment analysis on COVID-19 news tweets
نویسندگان
چکیده
Abstract This research utilizes a lexicon-based sentiment analysis to reveal the emotions conveyed by various news media and analyze differences among media. NRC Affect Intensity Lexicon is utilized; it provides of words in 8 categories emotions. The lexicon modified reflect context news, i.e., COVID-19 pandemic. Tweets are collected from four Indonesia’s three international English-language Each tweet assigned total emotion score for each scores averaged day obtain Daily Emotion. Based on Emotion, Dominant Emotion may be identified, with highest average particular date. visualization shows that dominant Indonesian-language Sadness Trust, while Fear Trust considerably more pronounced Furthermore, media, kompascom significantly intense than others Joy, Sadness, Fear, Trust. Among XHNews conveying Trust; timesofindia both most Joy. this concludes Mix different. also convey different levels intensity reporting news.
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ژورنال
عنوان ژورنال: IOP conference series
سال: 2021
ISSN: ['1757-899X', '1757-8981']
DOI: https://doi.org/10.1088/1757-899x/1077/1/012042