Social networking, distributed problem solving and human computation have gained high visibility. Wikipedia is a well established service that incorporates aspects of these three fields of research. For this reason it is a good object of study for determining quality of solutions in a social setting that is open, completely distributed, bottom up and not peer reviewed by certified experts. In particular, this paper aims at identifying semantic convergence of Wikipedia articles; the notion that the content of an article stays stable regardless of continuing edits. This could lead to an automatic recommendation of good article tags but also add to the usability of Wikipedia as a Web Service and to its reliability for information extraction. The methods used and the results obtained in this research can be generalized to other communities that iteratively produce textual content.
['Xueqi Cheng', 'Fuxin Ren', 'Xianbin Cao', 'Jing Ma']
How Contents Influence Clustering Features in the Web