Palavar, Yunus EmreÇelik, ZeynepAlbayrak, AhmetÖzçelik, EmineErdil, Mustafa2023-07-262023-07-2620229.78167E+12https://doi.org/10.1109/ICMI55296.2022.9873660https://hdl.handle.net/20.500.12684/12638IEEE Turkey Section;Istanbul Atlas University2nd International Conference on Computing and Machine Intelligence, ICMI 2022 -- 15 July 2022 through 16 July 2022 -- 182557In this study, sentiment analysis was conducted on the data of the Covid-19 epidemic process from the official twitter account of the Republic of Turkey Fahrettin Koca, Minister of Health, @drfahrettinkoca (SO) and the Twitter account of the @WHO (World Health Organization). First of all, twitter data was obtained and necessary arrangements were made for analysis. Then, tweets were shown with a word cloud and it was determined which words were used more frequently. Afterwards, sentiment analysis was performed on the data using the TextBlob library. In addition, it has been found out which subjects are focused on tweets sent from SO and @WHO (World Health Organization) accounts with the LDA algorithm. It has been seen that positive tweets were sent from both accounts, giving positive messages to the society. © 2022 IEEE.en10.1109/ICMI55296.2022.9873660info:eu-repo/semantics/closedAccessCovid-19Sentiment analysisTopic ModelingTwitter data analysisWordCloudHealthSocial networking (online)Covid-19Epidemic processSentiment analysisTopic ModelingTwitter data analyseWord cloudsWordcloudWorld Health OrganizationSentiment analysisConference Object2-s2.0-85138990670