@inproceedings{41357be34d6e450cacc617f22aadf6a3,
title = "Measuring twitter user similarity as a function of strength of ties",
abstract = "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.",
keywords = "Information retrieval, Microblogging, Social media, Social networks, Twitter",
author = "John Conroy and Josephine Griffith and Colm O'Riordan",
year = "2011",
language = "English",
isbn = "9789898425799",
series = "KDIR 2011 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval",
pages = "262--270",
booktitle = "KDIR 2011 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval",
note = "International Conference on Knowledge Discovery and Information Retrieval, KDIR 2011 ; Conference date: 26-10-2011 Through 29-10-2011",
}