Uncovering the social dynamics of online elections

Past work analysing elections in online domains has largely ignored the underlying social networks present in such environments. Here, the Wikipedia Request for Adminship (RfA) process is studied within the context of a social network and several factors influencing different stages of the voting process are pinpointed. Machine-learning problems were formulated to test the identified factors. The different facets explored are: election participation, decision making in elections, and election outcome. Our results show that voters tend to participate in elections that their contacts have participated in. Furthermore, there is evidence showing that an individual's decision-making is influenced by his contacts' actions. The properties of voters within the social graph were also studied; results reveal that candidates who gain the support of an influential coalition tend to succeed in elections. Additionally, detailed analyses on different classes of voters and candidates were made. Finally, the structural properties corresponding to networks of election participants were analysed and these networks were found to exhibit higher degrees of community structure versus graphs of participants selected at random.