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Authors: John Conroy ; Josephine Griffith and Colm O’Riordan

Affiliation: National University of Ireland, Ireland

ISBN: 978-989-8425-79-9

Keyword(s): Twitter, Social media, Microblogging, Information retrieval, Social networks.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Soft Computing ; Symbolic Systems ; User Profiling and Recommender Systems ; Web Mining

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.

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Paper citation in several formats:
Conroy, J.; Griffith, J. and O’Riordan, C. (2011). MEASURING TWITTER USER SIMILARITY AS A FUNCTION OF STRENGTH OF TIES.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011) ISBN 978-989-8425-79-9, pages 254-262. DOI: 10.5220/0003661902620270

@conference{kdir11,
author={John Conroy. and Josephine Griffith. and Colm O’Riordan.},
title={MEASURING TWITTER USER SIMILARITY AS A FUNCTION OF STRENGTH OF TIES},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)},
year={2011},
pages={254-262},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003661902620270},
isbn={978-989-8425-79-9},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)
TI - MEASURING TWITTER USER SIMILARITY AS A FUNCTION OF STRENGTH OF TIES
SN - 978-989-8425-79-9
AU - Conroy, J.
AU - Griffith, J.
AU - O’Riordan, C.
PY - 2011
SP - 254
EP - 262
DO - 10.5220/0003661902620270

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