基于词典的印尼COVID-19网络媒体新闻情感分析与情感检测

Bayu Waspodo, Nuryasin, Amalia Khaerunnisa Nursya Bany, Rinda Hesti Kusumaningtyas, Eri Rustamaji
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引用次数: 3

摘要

保持社交距离和隔离是新冠肺炎大流行的影响之一,这导致全国各地尤其是郊区的互联网用户增加。因此,媒体特别是网络媒体报道的新冠肺炎新闻将广泛传播。与此相关的关切之一是COVID-19新闻引发的情绪和情绪,这些情绪和情绪对于形成公众对COVID-19的看法和态度至关重要。因此,了解新冠肺炎新闻引发的情绪和情绪,有助于公众在通过网络媒体新闻寻求信息的过程中更加自觉。这项研究从2020年3月开始(基于公共卫生当局的公告)到2021年3月,使用了来自知名和流行网络媒体的19000多条COVID-19头条新闻。NRC情感词典用于从标题中检测情绪和情绪。分析结果表明,40%的标题引起了负面情绪。前七个月主要是负面情绪。尽管如此,在2020年底,积极情绪开始逐渐增加。悲伤、恐惧、信任和期待是新冠肺炎新闻引发的最主要情绪。负面情绪高涨与印尼因新冠肺炎导致的百万人死亡率无关。
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Indonesia COVID-19 Online Media News Sentiment Analysis with Lexicon-based Approach and Emotion Detection
Social distancing and isolation are one of the impacts of COVID-19 pandemic, which lead to the increase of internet users across the country especially in suburbs area. Consequently, news regarding COVID-19 reported by the media particularly online media would reach extensive masses. One of the concerns pertaining to this issue is the sentiments and emotions evoked by COVID-19 news, which those sentiments and emotions are crucial in shaping perceptions and attitudes of the public about COVID-19. Therefore, understanding the sentiments and emotions caused by COVID-19 news would help the public more aware in the process of seeking information through online media news. This research used more than 19.000 COVID-19 headlines from known and popular online media starting March 2020 (based on public health authority announcements) to March 2021. NRC Emotion Lexicon used to detect sentiments and emotions from the headlines. The result shown from the analysis stated that 40% of all the headlines evoked negative sentiments. The first seven months were dominated by negative sentiments. Although, at the end of the 2020 positive sentiment started increasing gradually. Sadness, Fear, Trust, and Anticipate were the most dominant emotions evoked by COVID-19 news. The high negative sentiment has no correlation with death-per-million because of COVID-19 in Indonesia.
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