Predicting the Future with Social Media
Bibliographic Data
| ID | 23319342 |
|---|---|
| Authors | Sitaram Asur (Hewlett-Packard (United States)), Bernardo A Huberman (0000-0002-6783-0864, Hewlett-Packard (United States)) |
| Year | 2010 |
| Pages | 492-499 |
| Publication date | 2010-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | CONFERENCE |
| Venue | 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (CONFERENCE) |
| Publisher | IEEE (PUBLISHER) |
| DOI | 10.1109/wi-iat.2010.63 |
| OpenAlex | W2015186536 |
| Language | EN |
| Citations received | 120 |
| References cited | 10 |
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.
Data science · Social media · World Wide Web · Complex Network Analysis Techniques · Computer Science · Data Stream Mining Techniques · Misinformation and Its Impacts
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| Unique citing works | 120 |
|---|---|
| Citations per year | 7,5 |
| Citation span | 2010 - 2025 (16) |
| Citation velocity | recent |
| Highly cited | Yes |
| Citation types | Neutral: 82 |