Crowdsourcing user studies with Mechanical Turk
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
FakeBook: Detecting Fake Profiles in On-Line Social Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
| Hi-index | 0.00 |
A malicious person could access a wealth of one's personal information by being one's 'friend' on a social networking site. The goal of this research is to understand the extent to which users are vulnerable to this tactic. Our experiment examined responses of users of a social networking site to a friendship request from a total stranger. Preliminary results indicate that a small but significant percentage of individuals are open to accepting such requests. The tendency to accept was higher when the request came from an unattractive person of the opposite sex. In the case of same-gender connections, however, the likelihood of acceptance was higher for attractive requesters. Moreover, the mere presence of a profile photo, regardless of gender and attractiveness of the requester, greatly increased the likelihood of request acceptance. However, individuals with higher privacy concerns showed a greater tendency to decline the request.