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  5. Finding useful users on twitter : twittomender the followee recommender
 
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Finding useful users on twitter : twittomender the followee recommender

Author(s)
Hannon, John  
McCarthy, Kevin  
Smyth, Barry  
Uri
http://hdl.handle.net/10197/3477
Date Issued
2011-04-21
Date Available
2012-02-03T12:03:47Z
Abstract
This paper examines an application for finding pertinent friends (followees) on Twitter. Whilst Twitter provides a great basis for receiving information, we believe a potential downfall lies in the lack of an effective way in which users of Twitter can find other Twitter users to follow. We apply several recommendation techniques to build a followee recommender for Twitter. We evaluate a variety of different recommendation strategies, using real-user data, to demonstrate the potential for this recommender system to correctly identify and promote interesting users who are worth following.
Sponsorship
Science Foundation Ireland
Other funder
Other Sponsorship
Amdocs Inc.
Type of Material
Conference Publication
Publisher
Springer
Copyright (Published Version)
Springer-Verlag Berlin Heidelberg 2011
Subjects

Twitter

Recommendation

Subject – LCSH
Online social networks
Twitter
Recommender systems (Information filtering);
DOI
10.1007/978-3-642-20161-5_94
Web versions
http://dx.doi.org/10.1007/978-3-642-20161-5_94
Language
English
Status of Item
Peer reviewed
Journal
Clough, P. et al. (eds.). Advances in Information Retrieval 33rd European Conference on IR Research, ECIR 2011, Dublin, Ireland, April 18-21, 2011. Proceedings
Conference Details
Presented at the 33rd European Conference on Information Retrieval (ECIR-11), DCU, Dublin, Ireland, April, 18-21, 2011
ISBN
978-3-642-20160-8
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
File(s)
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fulltext.pdf

Size

128.49 KB

Format

Adobe PDF

Checksum (MD5)

8fc159093d030ebfc54c18e05c96ae47

Owning collection
Computer Science Research Collection
Mapped collections
CLARITY Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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