Twitter Data Analysis: Izmir Earthquake Case

Authors : Özgür AĞRALİ, Hakan SÖKÜN, Enis KARAARSLAN

Pages : 36-41

View : 127 | Download : 24

Publication Date : 2022-12-31

Article Type : Research Paper

Abstract :Türkiye is located on a fault line; earthquakes often occur on a large and small scale. There is a need for effective solutions for gathering current information during disasters. We can use social media to get insight into public opinion. This insight can be used in public relations and disaster management. In this study, Twitter posts on İzmir Earthquake that took place on October 2020 are analyzed. We question if this analysis can be used to make social inferences on time. Data mining and natural language processing insert ignore into journalissuearticles values(NLP); methods are used for this analysis. NLP is used for sentiment analysis and topic modelling. The latent Dirichlet Allocation insert ignore into journalissuearticles values(LDA); algorithm is used for topic modelling. We used the Bidirectional Encoder Representations from Transformers insert ignore into journalissuearticles values(BERT); model working with Transformers architecture for sentiment analysis. It is shown that the users shared their goodwill wishes and aimed to contribute to the initiated aid activities after the earthquake. The users desired to make their voices heard by competent institutions and organizations. The proposed methods work effectively. Future studies are also discussed.
Keywords : Exploratory Data Analysis, Text Pre Processing, Disaster Management, Natural Language Processing, Social Media Analysis

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