Name
Abstract | ||
|---|---|---|
This paper describes the LiveTweet application, a system for automatically analysing and predicting the interestingness of microblog posts. Based on a stream of recent microblog posts the system tracks user interactions on Twitter that indicate interesting content. An incremental Naive Bayes model is trained to learn the characteristics of tweets which are considered interesting by the users. Finally, the probability of a microblog post to be retweeted is used as metric for its interestingness. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-28997-2_66 | ECIR |
Keywords | Field | DocType |
livetweet application,interesting content,interesting microblog post,recent microblog post,incremental naive bayes model,microblog post,user interaction | Data mining,World Wide Web,Social media,Information retrieval,Naive Bayes classifier,Computer science,Microblogging | Conference |
Citations | PageRank | References |
6 | 0.51 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arifah Che Alhadi | 1 | 144 | 7.72 |
| Thomas Gottron | 2 | 432 | 35.32 |
| Jérôme Kunegis | 3 | 874 | 51.20 |
| Nasir Naveed | 4 | 142 | 6.66 |