ליאור רוקח

Wikipedia, like other encyclopedias, includes biographies of notable people. However, because it is jointly written by many contributors, it is subject to constant manipulation by contributors attempting to add biographies of non-notable people. Over time, Wikipedia has developed inclusion criteria for notable people (e.g., receiving a significant award) based on which newly contributed biographies are evaluated. In this paper we present and analyze a set of simple indicators that can be used to predict which article will eventually be accepted. These indicators do not refer to the content itself, but to meta-content features (such as the number of categories that the biography is associated with) and to author-based features (such as if it is a first-time author). By training a classifier on these features, we successfully reached a high predictive performance (area under the receiver operating characteristic [ROC] curve [AUC] of 0.97) even though we overlooked the actual biography text.