The Possible Impact of Twitter Post Messages on Stock Market Activities

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dc.contributor.authorÖzparlak, Gerçek
dc.contributor.departmentSiyasal Bilgiler Fakültesitr_TR
dc.date.accessioned2021-10-05T08:50:03Z
dc.date.available2021-10-05T08:50:03Z
dc.date.issued2020-02-20
dc.description.abstractThe purpose of this research is to contribute to the academic field by demonstrating the relationship between stock related Twitter messages, their frequencies, sentiment analysis; stock return, volume, and volatility of Dow Jones Index and BIST30 & BIST100 Index. In this study, The Multinomial Naive Bayes Text Classifier is used as methodology since it is the most conventional method for text classification based on previous research. Using computational linguistics methods, 138.070 English and 34.632 Turkish tweets have been analyzed on a daily basis for a period of 8 months. The results demonstrated a strong relationship between tweets and their impact on the market. Moreover, according to results, there is a positive correlation between the number of retweets and BIST Volume lag-1 and lag+1. In addition, this article confirms that stock microblogs contain valuable information for investors and it can be an assistance in predicting the future market index.tr_TR
dc.identifier.endpage354tr_TR
dc.identifier.issn/e-issn1309-1034
dc.identifier.issue1tr_TR
dc.identifier.startpage335tr_TR
dc.identifier.urihttps://doi.org/10.33630/ausbf.589221tr_TR
dc.identifier.urihttp://hdl.handle.net/20.500.12575/75186
dc.identifier.volume75tr_TR
dc.language.isoentr_TR
dc.publisherAnkara Üniversitesitr_TR
dc.relation.isversionof10.33630/ausbf.589221tr_TR
dc.relation.journalAnkara Üniversitesi SBF Dergisitr_TR
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıtr_TR
dc.subjectTwitter Investor sentiment analysistr_TR
dc.subjectText classification Computational linguisticstr_TR
dc.subjectStock market predictiontr_TR
dc.titleThe Possible Impact of Twitter Post Messages on Stock Market Activitiestr_TR
dc.typeArticletr_TR

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