Mining Revision History to Assess Trustworthiness of Article Fragments

Abstract

Wikis are a type of collaborative repository system that enables users to create and edit shared content on the Web. The popularity and proliferation of Wikis have created a new set of challenges for trust research because the content in a Wiki can be contributed by a wide variety of users and can change rapidly. Nevertheless, most Wikis lack explicit trust management to help users decide how much they should trust an article or a fragment of an article. In this paper, we investigate the dynamic nature of revisions as we explore ways of utilizing revision history to develop an article fragment trust model. We use our model to compute trustworthiness of articles and article fragments. We also augment Wikis with a trust view layer with which users can visually identify text fragments of an article and view trust values computed by our model