delurking in online communities using repost behavior prediction method

Nowadays, with the advent of social networks, a big change has occurred in the structure of webbased services.online community (oc) enable their users to access different type of information, through the internet based structureanywhere any time. oc services are among the strategies used for production and repost of information by usersinterested in a specific area. in this respect, users become members in a particular domain at will and begin posting.considering the networking structure, one of the major challenges these groups face is the lack of reposting behavior.most users of these systems take up a lurking position toward the posts in the forum. delurking is a type of social mediabehavior where a user breaks an online silence or habit of passive thread viewing to engage in a virtual conversation.one of the proposed ways to improve delurking is the selection and display of influential posts for each individual.influential posts are so selected as to be more likely reposted by users based on each user's interests, knowledge andcharacteristics. the present article intends to introduce a new method for selecting k influential posts to ensure increasedrepost of information. in terms of participation in ocs, users are divided into two groups of posters and lurkers. somesolutions are proposed to encourage lurking users to participate in reposting the contents. based on actual data fromtwitter and actual blogs with respect to reposts, the assessments indicate the effectiveness of the proposed method.