The DOI matches its Crossref record; 16 of the 17 references it cites were found in a registry or an index.
Predicting the Future with Social Media
Open accessAbstract
In recent years, social media has become ubiquitous and important for social networking and content sharing. And yet, the content that is generated from these websites remains largely untapped. In this paper, we demonstrate how social media content can be used to predict real-world outcomes. In particular, we use the chatter from Twitter.com to forecast box-office revenues for movies. We show that a simple model built from the rate at which tweets are created about particular topics can outperform market-based predictors. We further demonstrate how sentiments extracted from Twitter can be further utilized to improve the forecasting power of social media.
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“Much research rests upon the assumption that online social traces reflect in some quantifiable way real-world phenomena (Asur and Huberman, 2010; Kıcıman and Richardson, 2015)”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Asur and Huberman, 2010
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Metadata
- Authors
- Asur, S., & Huberman, B. A.
- Affiliations
- Hewlett-Packard (United States) (US)
- Venue
- 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology
- Publisher
- IEEE
- Published
- 2010-08
- Pages
- 492-499
- OpenAlex
- W2015186536
- Cited by
- 2,081
- References
- 17
- Citations by year
- 2026: 12 · 2025: 36 · 2024: 52 · 2023: 71 · 2022: 90 · 2021: 129 · 2020: 168 · 2019: 156 · 2018: 165 · 2017: 196 · 2016: 184 · 2015: 243 · 2014: 205 · 2013: 173 · 2012: 111
- FWCI
- 269.17
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Funders
- National Science Foundation (0937060)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Keywords
- social media, Twitter, box office revenue, sentiment analysis, social media content
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