loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

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

Affiliation: National University of Ireland, Ireland

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.191.200.47

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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 (IC3K 2011) - KDIR; ISBN 978-989-8425-79-9; ISSN 2184-3228, SciTePress, 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 (IC3K 2011) - KDIR},
year={2011},
pages={254-262},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003661902620270},
isbn={978-989-8425-79-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2011) - KDIR
TI - MEASURING TWITTER USER SIMILARITY AS A FUNCTION OF STRENGTH OF TIES
SN - 978-989-8425-79-9
IS - 2184-3228
AU - Conroy, J.
AU - Griffith, J.
AU - O’Riordan, C.
PY - 2011
SP - 254
EP - 262
DO - 10.5220/0003661902620270
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic