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Using Twitter to Predict the Stock Market: Where is the Mood Effect?

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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Cited by:

  1. Yılmaz, Emrah Sıtkı & Ozpolat, Aslı & Destek, Mehmet Akif, 2022. "Do Twitter Sentiments Really Effective on Energy Stocks? Evidence from Intercompany Dependency," MPRA Paper 114155, University Library of Munich, Germany.
  2. Heba Ali, 2018. "Twitter, Investor Sentiment and Capital Markets: What Do We Know?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(8), pages 158-158, August.
  3. Silvia Garc'ia-M'endez & Francisco de Arriba-P'erez & Ana Barros-Vila & Francisco J. Gonz'alez-Casta~no, 2024. "Detection of Temporality at Discourse Level on Financial News by Combining Natural Language Processing and Machine Learning," Papers 2404.01337, arXiv.org.
  4. Li, Xin & Wen, Yang & Jiang, Jiaojiao & Daim, Tugrul & Huang, Lucheng, 2022. "Identifying potential breakthrough research: A machine learning method using scientific papers and Twitter data," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
  5. Fang Wang & Marko Gacesa, 2024. "Semi-strong Efficient Market of Bitcoin and Twitter: an Analysis of Semantic Vector Spaces of Extracted Keywords and Light Gradient Boosting Machine Models," Papers 2409.15988, arXiv.org.
  6. Bouteska, Ahmed & Ha, Le Thanh & Bhuiyan, Faruk & Sharif, Taimur & Abedin, Mohammad Zoynul, 2024. "Contagion between investor sentiment and green bonds in China during the global uncertainties," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 469-484.
  7. Ton, Thai & Leung, Henry & Gao, Yang & Schiereck, Dirk, 2024. "Agreeing to disagree: Informativeness of sentiments in internet message boards," Pacific-Basin Finance Journal, Elsevier, vol. 87(C).
  8. Costola, Michele & Hinz, Oliver & Nofer, Michael & Pelizzon, Loriana, 2023. "Machine learning sentiment analysis, COVID-19 news and stock market reactions," Research in International Business and Finance, Elsevier, vol. 64(C).
  9. Milla Siikanen & Kk{e}stutis Baltakys & Juho Kanniainen & Ravi Vatrapu & Raghava Mukkamala & Abid Hussain, 2017. "Facebook drives behavior of passive households in stock markets," Papers 1709.07300, arXiv.org, revised May 2018.
  10. Yingying Xu & Jichang Zhao, 2022. "Can sentiments on macroeconomic news explain stock returns? Evidence form social network data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2073-2088, April.
  11. Eryka Probierz & Adam Galuszka & Katarzyna Klimczak & Karol Jedrasiak & Tomasz Wisniewski & Tomasz Dzida, 2021. "Financial Sentiment on Twitter's Community and it's Connection to Polish Stock Market Movements in Context of Behavior Modelling," European Research Studies Journal, European Research Studies Journal, vol. 0(4 - Part ), pages 56-65.
  12. Stefan Stieglitz & Christian Meske & Björn Ross & Milad Mirbabaie, 2020. "Going Back in Time to Predict the Future - The Complex Role of the Data Collection Period in Social Media Analytics," Information Systems Frontiers, Springer, vol. 22(2), pages 395-409, April.
  13. Frank Z. Xing & Erik Cambria & Lorenzo Malandri & Carlo Vercellis, 2018. "Discovering Bayesian Market Views for Intelligent Asset Allocation," Papers 1802.09911, arXiv.org, revised Jun 2018.
  14. 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.
  15. repec:ers:journl:v:xxiv:y:2021:i:4b:p:56-65 is not listed on IDEAS
  16. Theophilos Papadimitriou & Periklis Gogas & Athanasios Fotios Athanasiou, 2020. "Forecasting S&P 500 spikes: an SVM approach," Digital Finance, Springer, vol. 2(3), pages 241-258, December.
  17. Jung, Sang Hoon & Jeong, Yong Jin, 2021. "Examining stock markets and societal mood using Internet memes," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
  18. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of Twitter sentiment on renewable energy stocks," Energy Economics, Elsevier, vol. 76(C), pages 153-169.
  19. Bowden, James & Gemayel, Roland, 2022. "Sentiment and trading decisions in an ambiguous environment: A study on cryptocurrency traders," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
  20. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
  21. Youzhu Li & Xianghui Gao & Mingying Du & Rui He & Shanshan Yang & Jason Xiong, 2020. "What Causes Different Sentiment Classification on Social Network Services? Evidence from Weibo with Genetically Modified Food in China," Sustainability, MDPI, vol. 12(4), pages 1-15, February.
  22. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
  23. Qing Liu & Hosung Son, 2024. "Data selection and collection for constructing investor sentiment from social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
  24. Liu, Keyan & Zhou, Jianan & Dong, Dayong, 2021. "Improving stock price prediction using the long short-term memory model combined with online social networks," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
  25. Perez, Charles & Sokolova, Karina & Konate, Malick, 2020. "Digital social capital and performance of initial coin offerings," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
  26. Rilwan Sakariyahu & Mohamed Sherif & Audrey Paterson & Eleni Chatzivgeri, 2021. "Sentiment‐Apt investors and UK sector returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3321-3351, July.
  27. Aditya Pandey & Haseeba Fathiya & Nivedita Patel, 2022. "Cross-Domain Shopping and Stock Trend Analysis," Papers 2212.14689, arXiv.org.
  28. Chen, Wen-Yi & Chen, Mei-Ping, 2022. "Twitter’s daily happiness sentiment, economic policy uncertainty, and stock index fluctuations," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  29. K Shiljas & Dilip Kumar & Hajam Abid Bashir, 2023. "Nexus between Twitter-based sentiment and tourism sector performance amid COVID-19 pandemic," Tourism Economics, , vol. 29(8), pages 2200-2205, December.
  30. Qadan, Mahmoud & Aharon, David Y. & Cohen, Gil, 2020. "Everybody likes shopping, including the US capital market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
  31. Liang, Chao & Wang, Lu & Duong, Duy, 2024. "More attention and better volatility forecast accuracy: How does war attention affect stock volatility predictability?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 1-19.
  32. Ryosuke Gotoh, 2024. "Analyzing the influence of web search behavior on electricity market price: a case study of Japan electric power exchange," Journal of Computational Social Science, Springer, vol. 7(1), pages 837-876, April.
  33. Teti, Emanuele & Dallocchio, Maurizio & Aniasi, Alberto, 2019. "The relationship between twitter and stock prices. Evidence from the US technology industry," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
  34. Lehrer, Steven & Xie, Tian & Zhang, Xinyu, 2021. "Social media sentiment, model uncertainty, and volatility forecasting," Economic Modelling, Elsevier, vol. 102(C).
  35. Chen, Rongda & Wang, Shengnan & Jin, Chenglu & Yu, Jingjing & Zhang, Xinyu & Zhang, Shuonan, 2023. "Comovements between multidimensional investor sentiment and returns on internet financial products," International Review of Financial Analysis, Elsevier, vol. 85(C).
  36. Francisco de Arriba-P'erez & Silvia Garc'ia-M'endez & Jos'e A. Regueiro-Janeiro & Francisco J. Gonz'alez-Casta~no, 2024. "Detection of financial opportunities in micro-blogging data with a stacked classification system," Papers 2404.07224, arXiv.org.
  37. Sophie Cockcroft & Mark Russell, 2018. "Big Data Opportunities for Accounting and Finance Practice and Research," Australian Accounting Review, CPA Australia, vol. 28(3), pages 323-333, September.
  38. Benjamin Clapham & Michael Siering & Peter Gomber, 2021. "Popular News Are Relevant News! How Investor Attention Affects Algorithmic Decision-Making and Decision Support in Financial Markets," Information Systems Frontiers, Springer, vol. 23(2), pages 477-494, April.
  39. Siikanen, Milla & Baltakys, Kęstutis & Kanniainen, Juho & Vatrapu, Ravi & Mukkamala, Raghava & Hussain, Abid, 2018. "Facebook drives behavior of passive households in stock markets," Finance Research Letters, Elsevier, vol. 27(C), pages 208-213.
  40. Wang, Fang & Gacesa, Marko, 2023. "Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models," International Review of Financial Analysis, Elsevier, vol. 88(C).
  41. Audrino, Francesco & Serwart, Jan, 2024. "Yield curve trading strategies exploiting sentiment data," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
  42. Qing Liu & Hosung Son, 2024. "Methods for aggregating investor sentiment from social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-22, December.
  43. Wang, Gang-Jin & Xiong, Lu & Zhu, You & Xie, Chi & Foglia, Matteo, 2022. "Multilayer network analysis of investor sentiment and stock returns," Research in International Business and Finance, Elsevier, vol. 62(C).
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