The Effects of Social Media Attention and Sentiment on Initial Public Offering Returns
DOI:
https://doi.org/10.47611/jsrhs.v10i4.2272Keywords:
Stock returns, Initial Public Offering, Twitter, Natural language processing, Sentiment analysisAbstract
Going public is a monumental step for many companies. Not only does it increase a company's legitimacy in the business community, but it also gives opportunities for them to harness significant amounts of investment capital. However, entrepreneurs and investors often face uncertainty due to the unpredictable nature of initial public offerings (IPOs). This study evaluated the impact of the amount and sentiment of Twitter activity on stock returns using data from domestic companies who went public from June 1, 2020 - May 31, 2021. Overall market behavior, company size, and community population demographics and social economic status of the companies' headquarters locations were controlled. The analyses showed that Twitter activity is associated with higher returns during relatively long-term time frames. The results are relevant for companies and potential IPO investors to predict and maximize their profits in the market. They also open opportunities for future research to investigate more in-depth regarding social factors in relation to IPOs.
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Albrecht, S., Lutz, B., & Neumann, D. (2019). How Sentiment Impacts the Success of Blockchain Startups – An Analysis of Social Media Data and Initial Coin Offerings. Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2019.551
Ashwini Athawale, M., & Deepali M. Gohil, M. (2018). Spam Detection on Collection of Twitter Data Using Naive Bayes Algorithm. International Journal of Innovative Research in Science, Engineering and Technology, 7(6). http://www.ijirset.com/upload/2018/june/60_10_Spam.PDF
Bartz-Beielstein, T., & Markon, S. (2004). Tuning search algorithms for real-world applications: A regression tree based approach. Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753), 1111–1118. https://doi.org/10.1109/CEC.2004.1330986
Baucom, C., Bate, J., Ochoa, S., Santos, I., Sergios, A., Lorentzen, L., & Reilly, K. (2019). The Epidemiology of the AIDS Pandemic: Historical, Cultural, Political, Societal Perspectives and Knowledge of HIV. Journal of Student Research, 8(2). https://doi.org/10.47611/jsr.v8i2.781
Benveniste, L. M., & Spindt, P. A. (1989). How investment bankers determine the offer price and allocation of new issues. Journal of Financial Economics, 24(2), 343–361. https://doi.org/10.1016/0304-405X(89)90051-2
Byrne, I., Kanaoka, Y., Pollack, N. E., Rhee, H. J., & Sommers, P. M. (2019). An Analysis of Airport Delays Across the United States, 2012-2018. Journal of Student Research, 8(2). https://doi.org/10.47611/jsr.v8i2.775
Chang, C., Chiang, Y.-M., Qian, Y., & Ritter, J. R. (2017). Pre-market Trading and IPO Pricing. The Review of Financial Studies, 30(3), 835–865. https://doi.org/10.1093/rfs/hhw032
Deeds, D. L., Decarolis, D., & Coombs, J. E. (1997). The impact of firmspecific capabilities on the amount of capital raised in an initial public offering: Evidence from the biotechnology industry. Journal of Business Venturing, 12(1), 31–46. https://doi.org/10.1016/S0883-9026(97)84970-1
Gerbershagen, H. J., Pogatzki-Zahn, E., Aduckathil, S., Peelen, L. M., Kappen, T. H., van Wijck, A. J. M., Kalkman, C. J., & Meissner, W. (2014). Procedure-specific Risk Factor Analysis for the Development of Severe Postoperative Pain. Anesthesiology, 120(5), 1237–1245. https://doi.org/10.1097/ALN.0000000000000108
Gian, L. G., Luca, M., Camilla Mazzoli, & Sabrina, S. (2020). The social side of IPOs: Twitter sentiment and investors attention in the IPO primary market. African Journal of Business Management, 14(12), 529–539. https://doi.org/10.5897/AJBM2020.9135
Guijarro, F., Moya-Clemente, I., & Saleemi, J. (2019). Liquidity Risk and Investors’ Mood: Linking the Financial Market Liquidity to Sentiment Analysis through Twitter in the S&P500 Index. Sustainability, 11(24), 7048. https://doi.org/10.3390/su11247048
Guilherme, B. (n.d.). Investing in Stock IPOs with Sentiment Analysis from Twitter optimized by Genetic Algorithms. https://www.semanticscholar.org/paper/Investing-in-Stock-IPOs-with-Sentiment-Analysis-by-Guilherme/23a12f6ab6cdb79b277d97476795ac1f3bb3ad9c#paper-header
Jagdale, R., Shirsat, V., & Deshmukh, S. (2016). Sentiment Analysis of Events from Twitter Using Open Source Tool. International Journal of Computer Science and Mobile Computing, 5(4), 475–485.
Krinitz, J., & Neumann, D. (2021). Market Engineering: Insights from Two Decades of Research on Market and Information. Springer. https://link.springer.com/content/pdf/10.1007%2F978-3-030-66661-3.pdf
Kusumawati, R., D’arofah, A., & Pramana, P. A. (2019). Comparison Performance of Naive Bayes Classifier and Support Vector Machine Algorithm for Twitter’s Classification of Tokopedia Services. Journal of Physics: Conference Series, 1320, 012016. https://doi.org/10.1088/1742-6596/1320/1/012016
Liew, J. K.-S., & Wang, G. Z. (2015). Twitter Sentiment and IPO Performance: A Cross-Sectional Examination. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2567295
Loughran, T., & McDonald, B. (2013). IPO first-day returns, offer price revisions, volatility, and form S-1 language. Journal of Financial Economics, 109(2), 307–326. https://doi.org/10.1016/j.jfineco.2013.02.017
M., V., Vala, J., & Balani, P. (2016). A Survey on Sentiment Analysis Algorithms for Opinion Mining. International Journal of Computer Applications, 133(9), 7–11. https://doi.org/10.5120/ijca2016907977
Narayanan, V., Arora, I., & Bhatia, A. (2013). Fast and Accurate Sentiment Classification Using an Enhanced Naive Bayes Model. In H. Yin, K. Tang, Y. Gao, F. Klawonn, M. Lee, T. Weise, B. Li, & X. Yao (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2013 (Vol. 8206, pp. 194–201). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-41278-3_24
Ranco, G., Aleksovski, D., Caldarelli, G., Grčar, M., & Mozetič, I. (2015). The Effects of Twitter Sentiment on Stock Price Returns. PLOS ONE, 10(9), e0138441. https://doi.org/10.1371/journal.pone.0138441
Tao, J., Deokar, A. V., & Deshmukh, A. (2018). Analysing forward-looking statements in initial public offering prospectuses: A text analytics approach. Journal of Business Analytics, 1(1), 54–70. https://doi.org/10.1080/2573234X.2018.1507604
Vetter, T. R., & Schober, P. (2018). Regression: The Apple Does Not Fall Far From the Tree. Anesthesia & Analgesia, 127(1), 277–283. https://doi.org/10.1213/ANE.0000000000003424
Wu, D. D., Zheng, L., & Olson, D. L. (2014). A Decision Support Approach for Online Stock Forum Sentiment Analysis. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(8), 1077–1087. https://doi.org/10.1109/TSMC.2013.2295353
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