Choudhury, Smitashree and Alani, Harith
(2014).
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| URL: | http://ceur-ws.org/Vol-1210/SP2014_04.pdf |
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| Google Scholar: | Look up in Google Scholar |
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 | ||||||
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| Copyright Holders: | 2014 The Authors | ||||||
| ISSN: | 1613-0073 | ||||||
| Project Funding Details: |
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| 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) |
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| Research Group: | Centre for Research in Computing (CRC) | ||||||
| Item ID: | 40840 | ||||||
| Depositing User: | Smitashree Choudhury | ||||||
| Date Deposited: | 19 Sep 2014 12:58 | ||||||
| Last Modified: | 02 May 2018 14:02 | ||||||
| URI: | http://oro.open.ac.uk/id/eprint/40840 | ||||||
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