Covid-19, oldukça bulaşıcı ve zararlı bir hastalıktır ve son yılların en yaygın sağlık krizlerinden biri olarak kabul edilmektedir. Pandemi, etkisini tüm dünyada hala sürdürmekte ve başlangıçta beklenenden daha uzun süredir devam etmektedir. Türkiye'de de pandemi insanları etkilemetkte ve endişelendirmektedir. Bu çalışmada ilk vakanın açıklandığı mart ayından normalleşme sürecinin başladığı haziran ayı (18 Mart- 28 Mayıs) arasındaki dönemde toplumun salgına olan tepkileri incelenmiştir. Bu tepkileri anlamak için Twitter platformunda #Evdekal hashtagini kullanan toplam 567.018 metin elde edilerek analiz edilmiştir. Pandeminin ilk ortaya çıktığı bu dönemde, metin madenciliği kullanılarak toplumun konuştukları anlamlandırılmaya çalışılmıştır. Duyarlılık analizi, bireylerin olumlu / olumsuz duygu durumlarını ve umut düzeylerini farklılaştıran haftalık tepkilerini görmek için kullanılmıştır. İki haftalık süreçler halinde analiz edilen duygularda bazı farklılıklar olduğu sonucuna ulaşılmıştır.
COVID-19 is a highly infectious and detrimental illness and is accepted as one of the most pervasive health crises of the last decades. The pandemic maintains its full effect and has continued longer than initially expected. The pandemic has affected many people in Turkey as well, irritating and making them anxious. In this study, the reaction of the society to the epidemic has been examined in the period from March month, when the first case has been announced, to June, when the normalization process began (18 March- 28 May). In order to understand these reactions, a total of 567,018 texts using the hashtag #StayHome on the Twitter platform have been fetched and analyzed. In this period, when the pandemic first appeared, it has been tried to make sense of what society has talked about by using text mining. Sensitivity analysis has been used to see the weekly reactions of individuals that differentiate their positive/negative moods and hope levels. As a result, some differences have been observed in the emotions analyzed in two-week periods.
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