Name
Title | ||
|---|---|---|
An author-reader influence model for detecting topic-based influencers in social media |
Abstract | ||
|---|---|---|
This work addresses the problem of detecting topic-based influencers in social media. For that end, we devise a novel behavioral model of authors and readers, where authors try to influence readers by generating ``\\emph{attractive}\" content, which is both \\emph{relevant} and \\emph{unique}, and readers can become authors themselves by further citing or referencing content made by other authors. The model is realized by means of a content-based citation graph, where nodes represent authors with their generated content and edges represent reader-to-author citations. To find the top influencers for a given topic, we first profile the content of authors (nodes) and citations (edges) and derive topic-based similarity scores to the topic, which further model the unique and relevant topic interests of users. We then present three different extensions of the Topic-Sensitive PageRank algorithm that exploit the similarity scores to find topic-based influencers. We evaluate our solution on a large real-world dataset that was gathered from Twitter by measuring information diffusion in social networks. We show that, overall, our methods outperform several state-of-the-art methods. This work further serves as an evidence that the topic uniqueness aspect in user interests within social media should be considered for the influencers detection task; this is in comparison to previous works that have solely focused on detecting topic-based influencers using the combination of link structure and topic-relevance. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2631775.2631804 | HT |
Keywords | Field | DocType |
information filtering,social media,topic-based influencers | Uniqueness,World Wide Web,Social media,Social network,Computer science,Behavioral modeling,Pagerank algorithm,Exploit,Citation graph,Multimedia,Influencer marketing | Conference |
Citations | PageRank | References |
9 | 0.55 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonathan Herzig | 1 | 9 | 0.55 |
| Yosi Mass | 2 | 574 | 60.91 |
| Haggai Roitman | 3 | 12 | 2.34 |