Abstract
Little is currently known about the factors that promote the propagation of information in online social networks following terrorist events. In this paper we took the case of the terrorist event in Woolwich, London in 2013 and built models to predict information flow size and survival using data derived from the popular social networking site Twitter. We define information flows as the propagation over time of information posted to Twitter via the action of retweeting. Following a comparison with different predictive methods, and due to the distribution exhibited by our dependent size measure, we used the zerotruncated negative binomial (ZTNB) regression method. To model survival, the Cox regression technique was used because it estimates proportional hazard rates for independent measures. Following a principal component analysis
to reduce the dimensionality of the data, social, temporal and content factors of the tweet were used as predictors in both models. Given the likely emotive
to reduce the dimensionality of the data, social, temporal and content factors of the tweet were used as predictors in both models. Given the likely emotive
| Original language | English |
|---|---|
| Article number | 206 |
| Number of pages | 14 |
| Journal | Social Network Analysis and Mining |
| Volume | 4 |
| Issue number | 1 |
| Early online date | 13 Jun 2014 |
| DOIs | |
| Publication status | Published - Jun 2014 |
Keywords
- Social network analysis
- Information flows
- Information propagation
- Information spreading
- Social media
- Sentiment analysis
- Opinion mining
- Predictive models
Access to Document
- burnap2014socnetwanalmin206
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