MEASURING TWITTER USER SIMILARITY AS A FUNCTION OF STRENGTH OF TIES

Users of online social networks reside in social graphs, where any given user-pair may be connected or unconnected. These connections may be formal or inferred social links; and may be binary or weighted. We might expect that users who are connected by a social tie are more similar in what they write than unconnected users, and that more strongly connected pairs of users are more similar again than less-strongly connected users, but this has never been formally tested. This work describes a method for calculating the similarity between twitter social entities based on what they have written, before examining the similarity between twitter user-pairs as a function of how tightly connected they are. We show that the similarity between pairs of twitter users is indeed positively correlated with the strength of the tie between them.