Network Effects on Tweeting
Online social networks (OSNs) have created new and exciting ways to connect and share information. Perhaps no site has had a more profound effect on information exchange than Twitter.com. In this paper, we study large-scale graph properties and lesser-studied local graph structures of the explicit social network and the implicit retweet network in order to better understand the relationship between socialization and tweeting behaviors. In particular, we first explore the interplay between the social network and user tweet topics and offer evidence that suggests that users who are close in the social graph tend to tweet about similar topics. We then analyze the implicit retweet network and find highly unreciprocal links and unbalanced triads. We also explain the effects of these structural patterns on information diffusion by analyzing and visualizing how URLs tend to be tweeted and retweeted. Finally, given our analyses of the social network and the retweet network, we provide some insights into the relationships between these two networks.
KeywordsData mining social networks information diffusion
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- 1.Bakshy, E., Hofman, J., Mason, W., Watts, D.: Identifying influencers on twitter. In: Fourth ACM International Conference on Web Seach and Data Mining (WSDM)Google Scholar
- 3.Castillo, C., Mendoza, M., Poblete, B.: Information credibility on twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp. 675–684. ACM, New York (2011)Google Scholar
- 4.Dodds, P., Harris, K., Kloumann, I., Bliss, C., Danforth, C.: Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter. Arxiv preprint arXiv:1101.5120 (2011)Google Scholar
- 5.Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a social network or a news media? In: Proceedings of the 19th International Conference on World Wide Web, pp. 591–600. ACM, New York (2010)Google Scholar
- 6.Lichtenwalter, R., Chawla, N.: DisNet: A Framework for Distributed Graph ComputationGoogle Scholar
- 8.Romero, D., Meeder, B., Kleinberg, J.: Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp. 695–704. ACM, New York (2011)Google Scholar
- 10.Wu, S., Hofman, J., Mason, W., Watts, D.: Who says what to whom on twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp. 705–714. ACM, New York (2011)Google Scholar