Terms of a feather : content-based news discovery and recommendation using Twitter

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dc.contributor.author Phelan, Owen
dc.contributor.author McCarthy, Kevin
dc.contributor.author Smyth, Barry
dc.contributor.author Bennett, Mike en
dc.date.accessioned 2011-05-24T12:04:51Z
dc.date.available 2011-05-24T12:04:51Z
dc.date.copyright Springer-Verlag, 2011 en
dc.date.issued 2011-04-19
dc.identifier.isbn 978-3-642-20160-8 en
dc.identifier.uri http://hdl.handle.net/10197/2950
dc.description Paper presented at the 33rd European Conference on Information Retrieval (ECIR-11), 18-21 April, 2010, DCU, Dublin, Ireland en
dc.description.abstract User-generated content has dominated the web’s recent growth and today the so-called real-time web provides us with unprecedented access to the real-time opinions, views, and ratings of millions of users. For example, Twitter’s 200m+ users are generating in the region of 1000+ tweets per second. In this work, we propose that this data can be harnessed as a useful source of recommendation knowledge. We describe a social news service called Buzzer that is capable of adapting to the conversations that are taking place on Twitter to ranking personal RSS subscriptions. This is achieved by a content-based approach of mining trending terms from both the public Twitter timeline and from the timeline of tweets published by a user’s own Twitter friend subscriptions. We also present results of a live-user evaluation which demonstrates how these ranking strategies can add better item filtering and discovery value to conventional recency-based RSS ranking techniques. en
dc.description.sponsorship Science Foundation Ireland en
dc.description.uri Conference website en
dc.description.uri http://www.ecir2011.dcu.ie/ en
dc.format.extent 851629 bytes
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Springer en
dc.relation.ispartof Clough, P.; Foley, C.; Gurrin, C.; Jones, G.J.F.; Kraaij, W.; Lee, H.; Murdoch, V. (eds.). Advances in Information Retrieval : 33rd European Conference on IR Resarch, ECIR 2011, Dublin, Ireland, April 18-21, 2011, Proceedings en
dc.relation.requires CLARITY Research Collection en
dc.rights The final publication is available at springerlink.com en
dc.subject User generated content en
dc.subject Real time web en
dc.subject Twitter en
dc.subject Recommendation en
dc.subject.lcsh Recommender systems (Information filtering) en
dc.subject.lcsh Social media en
dc.subject.lcsh User-generated content en
dc.subject.lcsh Twitter en
dc.title Terms of a feather : content-based news discovery and recommendation using Twitter en
dc.type Conference Publication en
dc.internal.availability Full text available en
dc.internal.webversions http://dx.doi.org/10.1007/978-3-642-20161-5_44 en
dc.status Peer reviewed en
dc.identifier.doi 10.1007/978-3-642-20161-5_44 en
dc.neeo.contributor Phelan|Owen|aut| en
dc.neeo.contributor McCarthy|Kevin|aut| en
dc.neeo.contributor Smyth|Barry|aut| en
dc.neeo.contributor Bennett|Mike|aut| en
dc.description.admin To be published by Springer LNCS http://www.ecir2011.dcu.ie/submitting/guidelines/ - 12M embargo AV 12/05/2011 Published version found July 2011, embargo until July 2012 - OR 14/07/2011 en

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