摘要
With the development of online social networks,a special group of online users named organized posters(or Internet water army,Internet paid posters in some literatures) have fl ooded the social network communities. They are organized in groups to post with specific purposes and sometimes even confuse or mislead normal users.In this paper,we study the individual and group characteristics of organized posters. A classifier is constructed based on the individual and group characteristics to detect them. Extensive experimental results on three real datasets demonstrate that our method based on individual and group characteristics using SVM model(IGCSVM) is effective in detecting organized posters and better than existing methods. We take a first look at finding the promoters based on the detected organized posters of our IGCSVM method. Our experiments show that it is effective in detecting promoters.
With the development of online social networks,a special group of online users named organized posters(or Internet water army,Internet paid posters in some literatures) have fl ooded the social network communities. They are organized in groups to post with specific purposes and sometimes even confuse or mislead normal users.In this paper,we study the individual and group characteristics of organized posters. A classifier is constructed based on the individual and group characteristics to detect them. Extensive experimental results on three real datasets demonstrate that our method based on individual and group characteristics using SVM model(IGCSVM) is effective in detecting organized posters and better than existing methods. We take a first look at finding the promoters based on the detected organized posters of our IGCSVM method. Our experiments show that it is effective in detecting promoters.
基金
supported by 973 Program of China(Grant No.2013CB329601, 2013CB329602,2013CB329604)
NSFC of China(Grant No.60933005,91124002)
863 Program of China(Grant No.2012AA01A401, 2012AA01A402)
National Key Technology RD Program of China(Grant No.2012BAH38B04, 2012BAH38B06)