Name
Abstract | ||
|---|---|---|
Use of online social networks has grown dramatically since the first Web 2.0 technologies were deployed in the early 2000s. Our ability to capture user data, in particular behavioral data has grown in concert with increased use of these social systems. In this study, we survey methods for modeling and analyzing online user behavior. We focus on negative behaviors (social spamming and cyberbullying) and mitigation techniques for these behaviors. We also provide information on the interplay between privacy and deception in social networks and conclude by looking at trending and cascading models in social media. (C) 2017 John Wiley & Sons, Ltd |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1002/widm.1203 | WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY |
Field | DocType | Volume |
Graph,Social network,Computer science,Artificial intelligence,Behavioral analysis,Machine learning | Journal | 7.0 |
Issue | ISSN | Citations |
3.0 | 1942-4787 | 1 |
PageRank | References | Authors |
0.35 | 14 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anna Cinzia Squicciarini | 1 | 1301 | 106.30 |
| Sarah Michele Rajtmajer | 2 | 31 | 10.06 |
| Christopher Griffin | 3 | 58 | 11.43 |