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Personal life event detection from social media

Choudhury, Smitashree and Alani, Harith (2014). Personal life event detection from social media. In: Workshop Proceedings, CEUR.

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Abstract

Creating video clips out of personal content from social media is on the rise. MuseumOfMe, Facebook Lookback, and Google Awesome are some popular examples. One core challenge to the creation of such life summaries is the identification of personal events, and their time frame. Such videos can greatly benefit from automatically distinguishing between social media content that is about someone's own wedding from that week, to an old wedding, or to that of a friend. In this paper, we describe our approach for identifying a number of common personal life events from social media content (in this paper we have used Twitter for our test), using multiple feature-based classifiers. Results show that combination of linguistic and social interaction features increases overall classification accuracy of most of the events while some events are relatively more difficult than others (e.g. new born with mean precision of .6 from all three models).

Item Type: Conference or Workshop Item
Copyright Holders: 2014 The Authors
ISSN: 1613-0073
Project Funding Details:
Funded Project NameProject IDFunding Body
Reel Lives: personal documentaries constructed from digital data.EP/L004062/1EPSRC (Engineering and Physical Sciences Research Council)
Extra Information: Edited by Federica Cena, Altigran Soares da Silva, Christoph Trattner
Keywords: Social Web; social media; event detection; personal life events
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Centre for Policing Research and Learning (CPRL)
Item ID: 40840
Depositing User: Smitashree Choudhury
Date Deposited: 19 Sep 2014 12:58
Last Modified: 06 Oct 2016 09:08
URI: http://oro.open.ac.uk/id/eprint/40840
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