The a-symmetry of activity in virtual communities is of great interest. While participation in the activities of virtual communities is crucial for a community's survival and development, many people prefer lurking, that is passive attention over active participation. Often, lurkers are the vast majority. There could be many reasons for lurking. Lurking can be measured and perhaps affected by both dispositional and situational variables. This project investigates social and cultural capital situational antecedents of lurking and de-lurking. We propose a novel way of measuring such capital, lurking, and de-lurking. We try to figure out what are the triggers to active participation. We try to answer this by mathematically defining a social communication network of activities in authenticated discussion forums. Authenticated discussion forums provide exact log information about every participant's activities and allow us to identify lurkers that become first time posters. The proposed Social Communication Network approach (SCN) is an extension of the traditional social network methodology to include, beyond human actors, discussion topics (e.g. Usenet newsgroups threads) and subjects of discussions (e.g. Usenet groups) as well. In addition the Social Communication Network approach distinguishes between READ and POST link types. These indicate active participation on the part of the human actor. We attempt to validate this model by examining the SCN using data collected in a sample of 82 online forums. By analyzing a graph structure of the network at moments of initial postings we verify several hypotheses about causes of de-lurking and provide some directions towards measuring active participation in virtual communities.
|Number of pages||10|
|Journal||Proceedings of the Hawaii International Conference on System Sciences|
|State||Published - 2004|
|Event||Proceedings of the Hawaii International Conference on System Sciences - Big Island, HI., United States|
Duration: 5 Jan 2004 → 8 Jan 2004
ASJC Scopus subject areas
- Computer Science (all)