The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Widespread Worry and the Stock Market
Open accessAbstract
Our emotional state influences our choices. Research on how it happens usually comes from the lab. We know relatively little about how real world emotions affect real world settings, like financial markets. Here, we demonstrate that estimating emotions from weblogs provides novel information about future stock market prices. That is, it provides information not already apparent from market data. Specifically, we estimate anxiety, worry and fear from a dataset of over 20 million posts made on the site LiveJournal. Using a Granger-causal framework, we find that increases in expressions of anxiety, evidenced by computationally-identified linguistic features, predict downward pressure on the S&P 500 index. We also present a confirmation of this result via Monte Carlo simulation. The findings show how the mood of millions in a large online community, even one that primarily discusses daily life, can anticipate changes in a seemingly unrelated system. Beyond this, the results suggest new ways to gauge public opinion and predict its impact.
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Cites
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Feeling and thinking: Preferences need no inferences.
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Giving content to investor sentiment: The role of media in the stock market
TETLOCK, P. C. (2007) · The Journal of Finance · doi:10.1111/j.1540-6261.2007.01232.x · Cited by 4,827
Investigating Causal Relations by Econometric Models and Cross-Spectral Methods
Granger, C. W. J. (2010) · Essays in Econometrics · doi:10.1017/cbo9780511753978.002 · Cited by 4,762
Fowler, J. H., & Christakis, N. A. (2008) · BMJ · doi:10.1136/bmj.a2338 · Cited by 1,990
Emotion, cognition, and behavior
Dolan, R. J. (2002) · Science · doi:10.1126/science.1076358 · Cited by 1,979
Heart Strings and Purse Strings: Carryover Effects of Emotions on Economic Decisions
Lerner, J. S., Small, D. A., & Loewenstein, G. (2004) · Psychological Science · doi:10.1111/j.0956-7976.2004.00679.x · Cited by 959
A Social Network Contagion Theory of Risk Perception
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Cited by
Twitter mood predicts the stock market
Bollen, J., Mao, H., & Zeng, X. (2011) · Journal of Computational Science · doi:10.1016/j.jocs.2010.12.007 · Cited by 5,206
“Over the past 5 years significant progress has been made in sentiment tracking techniques that extract indicators of public mood directly from social media content such as blog content [10], [12], [15], [17] and in particular large-scale Twitter feeds [22].”
BackgroundFrom Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series
O'Connor, B., Balasubramanyan, R., Routledge, B., & Smith, N. (2010) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v4i1.14031 · Cited by 1,923
Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data
Mao, H., Counts, S., & Bollen, J. (2011) · arXiv · doi:10.48550/arxiv.1112.1051 · Cited by 145
The tweets they are a-changin': Evolution of twitter users and behavior
Liu, Y., Kliman-Silver, C., & Mislove, A. (2014) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v8i1.14508 · Cited by 126
Cashtag Piggybacking: Uncovering Spam and Bot Activity in Stock Microblogs on Twitter
Cresci, S., Lillo, F., Regoli, D., Tardelli, S., & Tesconi, M. (2019) · ACM Transactions on the Web · doi:10.1145/3313184 · Cited by 105
Metadata
- Authors
- Gilbert, E., & Karahalios, K.
- Venue
- Proceedings of the International AAAI Conference on Web and Social Media
- Published
- 2010-05-16
- Volume
- 4
- Issue
- 1
- Pages
- 58-65
- ISSN
- 2162-3449 (ISSN-L)
- 2334-0770
- OpenAlex
- W1508206474
- Cited by
- 283
- References
- 9
- FWCI
- 38.54
- Type
- conference paper
- Language
- en
- Open access
- diamond
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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