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Mining Affective Context in Short Films for Emotion-Aware Recommendation

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Author(s)
Orellana-Rodriguez, Claudia 
Díaz-Aviles, Ernesto 
Nejdl, Wolfgang 
Uri
http://hdl.handle.net/10197/7235
Date Issued
04 September 2015
Date Available
23T12:34:18Z November 2015
Abstract
Emotion is fundamental to human experience and impactsour daily activities and decision-making processes where,e.g., the affective state of a user influences whether or notshe decides to consume a recommended item movie, book,product or service. However, information retrieval and recommendationtasks have largely ignored emotion as a sourceof user context, in part because emotion is difficult to measureand easy to misunderstand. In this paper we explore therole of emotions in short films and propose an approach thatautomatically extracts affective context from user commentsassociated to short films available in YouTube, as an alternativeto explicit human annotations. We go beyond the traditionalpolarity detection (i.e., positive/negative), and extractfor each film four opposing pairs of primary emotions:joysadness, angerfear, trustdisgust, and anticipationsurprise. Finally, in our empirical evaluation, we show howthe affective context extracted automatically can be leveragedfor emotion-aware film recommendation.
Other Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2015 the Authors
Keywords
  • Machine learning

  • Statistics

  • Computational social ...

  • Sentiment analysis

  • Social media analytic...

  • YouTube

DOI
10.1145/2700171.2791042
Language
English
Status of Item
Peer reviewed
Description
Proceedings of the 26th ACM Conference on Hypertext and Social Media, Middle East Technical University Northern Cyprus Campus, Cyprus, 1-4 September 2015
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Insight Research Collection
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