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A Sentiment Analysis of Twitter Content as a Predictor of Exchange Rate Movements

Author

Listed:
  • Serda Selin Ozturk

    (Istanbul Bilgi University)

  • Kursad Ciftci

    (Istanbul Bilgi University)

Abstract

Recently, social media, particularly microblogs, have become highly valuable information resources for many investors. Previous studies examined general stock market movements, whereas in this paper, USD/TRY currency movements based on the change in the number of positive, negative and neutral tweets are analyzed. We investigate the relationship between Twitter content categorized as sentiments, such as Buy, Sell and Neutral, with USD/TRY currency movements. The results suggest that there exists a relationship between the number of tweets and the change in USD/TRY exchange rate.

Suggested Citation

  • Serda Selin Ozturk & Kursad Ciftci, 2014. "A Sentiment Analysis of Twitter Content as a Predictor of Exchange Rate Movements," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, vol. 6(2), pages 132-140, December.
    • Handle: RePEc:ren:journl:v:6:y:2014:i:2:p:132-140
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    Citations

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    Cited by:

    1. Omotosho, Babatunde S. & Tumala, Mohammed M., 2019. "A Text Mining Analysis of Central Bank Monetary Policy Communication in Nigeria," MPRA Paper 98850, University Library of Munich, Germany.
    2. Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021. "Strength of words: Donald Trump's tweets, sanctions and Russia's ruble," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
    3. Chi-Wei Su & Xu-Yu Cai & Ran Tao, 2020. "Can Stock Investor Sentiment Be Contagious in China?," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    4. Omotosho, Babatunde S., 2020. "Central Bank Communication during Economic Recessions: Evidence from Nigeria," MPRA Paper 99655, University Library of Munich, Germany.
    5. Srinaath Anbu Durai & Wang Zhaoxia, 2023. "Sentiment Analysis, Social Media and Urban Economics: The Case of Singaporean HDB and Covid-19," International Journal of Innovation and Economic Development, Inovatus Services Ltd., vol. 9(5), pages 28-39, December.

    More about this item

    Keywords

    Sentiment Analysis; Social Media; Foreign Exchange Markets; Data Mining;
    All these keywords.

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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