Social Proof: The Impact of Author Traits on Influence Detection

Abstract

It has been claimed that people are more likely to be influenced by those who are similar to them than those who are not. In this paper, we test this hypothesis by measuring the impact of author traits on the detection of influence. The traits we explore are age, gender, religion, and political party. We create a single classifier to detect the author traits of each individual. We then use the personal traits predicted by this classifier to predict the influence of contributors in a Wikipedia Talk Page corpus. Our research shows that the influencer tends to have the same traits as the majority of people in the conversation. Furthermore, we show that this is more pronounced when considering the personal traits most relevant to the conversation. Our research thus provides evidence for the theory of social proof.