Abstract
Thebehaviours and shares of social media users have recently been closely followed by governments, institutions and companies. GovernmentsZcompanies determine some of their strategies by processing the “big data” created by the shares made by users.
Big data analysis has been used extensively lately. During the pandemic period, people shared their ideas and experiences on social media platforms. Twitter is one of the most popular worldwide Online Social Network (OSN). One of these sharing platforms is Twitter Social Media Platform. In this study, between 1 and 31 May 2020, user posts containing keywords related to COVID- 19 were collected. The analysis of the shares was made using natural language processing and text mining techniques on the corpus. In this paper, we use topic identification and sentiment analysis to explore a large number of tweets in Turkey. We investigate 19.199.490 tweets in Turkish, and we analyse comparing the effectiveness of topic identification and sentiment analysis in the messages in pandemic days.Keywords Natural language processing ∙ Data analysis ∙ Text mining ∙ Data visualization ∙ Social networks ∙ Twitter ∙ Survey ∙ Social graph ∙ Sentiment analysis ∙ Pandemic ∙ Economics of COVID-19 pandemic
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