LDA Topic Modeling on Twitter Data Concerning Immigrants and Refugees | IEEE Conference Publication | IEEE Xplore

LDA Topic Modeling on Twitter Data Concerning Immigrants and Refugees


Abstract:

In this study, the attitudes and opinions of Twitter users in Turkey towards immigrants have been examined to see how people express their thoughts and opinions about imm...Show More

Abstract:

In this study, the attitudes and opinions of Twitter users in Turkey towards immigrants have been examined to see how people express their thoughts and opinions about immigrants in Turkey and whether there are any dominant and interpretable topics that emerge. After a comprehensive pre-preprocessing, latent themes in the tweets are discovered using the Latent Dirichlet Allocation (LDA) topic modeling methodology. As the result of this analysis, 14 topics have emerged as meaningful and interpretable. The study is done over a small dataset and is somewhat limited; however, the results can shed light on the perspectives of Twitter users towards immigrants and refugees.
Date of Conference: 05-08 July 2023
Date Added to IEEE Xplore: 28 August 2023
ISBN Information:
Print on Demand(PoD) ISSN: 2165-0608
Conference Location: Istanbul, Turkiye

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