Abstract
Different measures have been proposed to predict whether individuals will adopt a new behavior in online social networks, given the influence produced by their neighbors. In this paper, we show one can achieve significant improvement over these standard measures, extending them to consider a pair of time constraints. These constraints provide a better proxy for social influence, showing a stronger correlation to the probability of influence as well as the ability to predict influence.
| Original language | English (US) |
|---|---|
| Title of host publication | Social, Cultural, and Behavioral Modeling - 10th International Conference, SBP-BRiMS 2017, Proceedings |
| Publisher | Springer Verlag |
| Pages | 254-261 |
| Number of pages | 8 |
| Volume | 10354 LNCS |
| ISBN (Print) | 9783319602394 |
| DOIs | |
| State | Published - 2017 |
| Event | 10th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2017 - Washington, United States Duration: Jul 5 2017 → Jul 8 2017 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10354 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 10th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2017 |
|---|---|
| Country | United States |
| City | Washington |
| Period | 7/5/17 → 7/8/17 |
Fingerprint
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Temporal analysis of influence to predict users’ adoption in online social networks. / Marin, Ericsson; Guo, Ruocheng; Shakarian, Paulo.
Social, Cultural, and Behavioral Modeling - 10th International Conference, SBP-BRiMS 2017, Proceedings. Vol. 10354 LNCS Springer Verlag, 2017. p. 254-261 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10354 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Temporal analysis of influence to predict users’ adoption in online social networks
AU - Marin, Ericsson
AU - Guo, Ruocheng
AU - Shakarian, Paulo
PY - 2017
Y1 - 2017
N2 - Different measures have been proposed to predict whether individuals will adopt a new behavior in online social networks, given the influence produced by their neighbors. In this paper, we show one can achieve significant improvement over these standard measures, extending them to consider a pair of time constraints. These constraints provide a better proxy for social influence, showing a stronger correlation to the probability of influence as well as the ability to predict influence.
AB - Different measures have been proposed to predict whether individuals will adopt a new behavior in online social networks, given the influence produced by their neighbors. In this paper, we show one can achieve significant improvement over these standard measures, extending them to consider a pair of time constraints. These constraints provide a better proxy for social influence, showing a stronger correlation to the probability of influence as well as the ability to predict influence.
UR - http://www.scopus.com/inward/record.url?scp=85022343112&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85022343112&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-60240-0_31
DO - 10.1007/978-3-319-60240-0_31
M3 - Conference contribution
SN - 9783319602394
VL - 10354 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 254
EP - 261
BT - Social, Cultural, and Behavioral Modeling - 10th International Conference, SBP-BRiMS 2017, Proceedings
PB - Springer Verlag
ER -