Sentiment Analysis Dataset on COVID-19 Variant News: Kumpulan Data Analisis Sentimen pada Berita Varian COVID-19 - Fakhri Muhammad; Nana Mulyana Maghfur; Apriade Voutama (Universitas Singaperbangsa Karawang, 2022)
The development of technology at this time is getting faster and faster, this is indicated by the number of emerging social media such as Facebook, Instagram, Twitter. Twitter is used as a forum for users to discuss, express opinions, and share stories between users, because many people today often have opinions about the COVID-19 outbreak, plus there are new variants that make people express various types of opinions, both good and bad. good and so on. Therefore, an effort was made to research the covid variant to see labeling sentiment, which in essence is a text mining process that aims to extract sentiment from text using regular expressions so that labels are obtained for each text in the dataset, so a dataset is formed that can be used for further research. The process includes data collection including (scrapping tweets, data tweets), pre-processing (case folding, remove URLs, remove stop words, change into standard words, stemming, tokenization), sentiment labeling (IR in the form of regular expressions, sentiment labeling), and data visualization show pie chart, show word cloud). Of the 8993 tweets that have been analyzed, 2213 positive tweets, 1735 negative tweets, and 5045 neutral tweets were found.