Abstract:
Wikipedia is no doubt one of the most important collaborative informational products of human history. The collaborative effort that produces Wikipedia is of fundamental importance because the community includes anonymous, uncompensated editors and a lack of observable top-down hierarchy. In this study, we propose an agent-based model for Wikipedia users’ activity of collaborative article editing. In this graph-theoretical approach every user and article are represented as vertices in a multimodal affiliation network. When a user chooses to edit an article, an edge between the node of the user in question and that of the edited article, is created. User preferences, statuses, relative content quality of articles, distribution of collaboration and resulting relationships are examined in the network. We analyse input parameters’ effects on resulting principal graph characteristics, namely the clustering coefficient, the path length, the small world characteristic Q, degree correlation, and degree distribution. Simulation findings point out that, users’ area of interest dimensions and active user percentage are positively correlated with the total edge count in the graph; therefore, the encyclopaedia quality. Conversely, good article threshold parameters raise high-quality article specifications and are negatively correlated with the total edit count in the encyclopaedia. We recommend an easier, automated process for the selection of good and featured articles of Wikipedia. Experiments have demonstrated that lowering the barrier of high quality status for articles, results in more effort and quality for the encyclopaedia as a whole. Additionally, we recommend more internal link concentration in good and featured articles, in order to spread the effort of their successful editors.
