Name
Abstract | ||
|---|---|---|
Measuring the strength of ties has been a fundamental task for a long time. However, most of previous work treated it as classifying a tie as strong or weak and were not able to quantitatively estimate the strength, which limits their scope of contribution. To tackle the problem, through leveraging user similarities and social interactions, we propose a latent variable model to calculate a continuous value that measures the strength. By bringing real users as judge, we demonstrate that the proposed method can outperform previous methods. Further, we utilize it to measure the strength of ties among a large set of microblogging users, and conduct statistical analysis on triads. We find that comparing to other types of triads, the one with three significantly strong ties are more likely to be created, which verifies the theory of sociology. © 2013 Springer-Verlag. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-37401-2_30 | APWeb |
Field | DocType | Volume |
Data science,Data mining,Social network,Social media,Computer science,Latent variable model,Microblogging,Statistical analysis | Conference | 7808 LNCS |
Issue | ISSN | Citations |
null | 16113349 | 2 |
PageRank | References | Authors |
0.36 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dakui Sheng | 1 | 2 | 0.36 |
| Tao Sun | 2 | 120 | 15.48 |
| Sheng Wang | 3 | 49 | 8.26 |
| Ziqi Wang | 4 | 47 | 4.63 |
| Ming Zhang | 5 | 1963 | 107.42 |