TY - GEN
T1 - Positive influence dominating set in online social networks
AU - Wang, Feng
AU - Camacho, Erika
AU - Xu, Kuai
PY - 2009
Y1 - 2009
N2 - Online social network has developed significantly in recent years as a medium of communicating, sharing and disseminating information and spreading influence. Most of current research has been on understanding the property of online social network and utilizing it to spread information and ideas. In this paper, we explored the problem of how to utilize online social networks to help alleviate social problems in the physical world, for example, the drinking, smoking, and drug related problems. We proposed a Positive Influence Dominating Set (PIDS) selection algorithm and analyzed its effect on a real online social network data set through simulations. By comparing the size and the average positive degree of PIDS with those of a 1-dominating set, we found that by strategically choosing 26% more people into the PIDS to participate in the intervention program, the average positive degree increases by approximately 3.3 times. In terms of the application, this result implies that by moderately increasing the participation related cost, the probability of positive influencing the whole community through the intervention program is significantly higher. We also discovered that a power law graph has empirically larger dominating sets (both the PIDS and 1-dominating set) than a random graph does.
AB - Online social network has developed significantly in recent years as a medium of communicating, sharing and disseminating information and spreading influence. Most of current research has been on understanding the property of online social network and utilizing it to spread information and ideas. In this paper, we explored the problem of how to utilize online social networks to help alleviate social problems in the physical world, for example, the drinking, smoking, and drug related problems. We proposed a Positive Influence Dominating Set (PIDS) selection algorithm and analyzed its effect on a real online social network data set through simulations. By comparing the size and the average positive degree of PIDS with those of a 1-dominating set, we found that by strategically choosing 26% more people into the PIDS to participate in the intervention program, the average positive degree increases by approximately 3.3 times. In terms of the application, this result implies that by moderately increasing the participation related cost, the probability of positive influencing the whole community through the intervention program is significantly higher. We also discovered that a power law graph has empirically larger dominating sets (both the PIDS and 1-dominating set) than a random graph does.
UR - http://www.scopus.com/inward/record.url?scp=70350655436&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70350655436&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-02026-1_29
DO - 10.1007/978-3-642-02026-1_29
M3 - Conference contribution
AN - SCOPUS:70350655436
SN - 3642020259
SN - 9783642020254
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 313
EP - 321
BT - Combinatorial Optimization and Applications - Third International Conference, COCOA 2009, Proceedings
T2 - 3rd International Conference on Combinatorial Optimization and Applications, COCOA 2009
Y2 - 10 June 2009 through 12 June 2009
ER -