Multimodal Sentiment Analysis of Social Media

Maynard, Diana, Dupplaw, David and Hare, Jonathon (2013) Multimodal Sentiment Analysis of Social Media. BCS SGAI Workshop on Social Media Analysis.

Record type: Conference or Workshop Item (Paper)

Abstract

This paper describes the approach we take to the analysis of social media, combining opinion mining from text and multimedia (images, videos, etc), and centred on entity and event recognition. We examine a particular use case, which is to help archivists select material for inclusion in an archive of social media for preserving community memories, moving towards structured preservation around semantic categories. The textual approach we take is rule-based and builds on a number of sub-components, taking into account issues inherent in social media such as noisy ungrammatical text, use of swear words, sarcasm etc. The analysis of multimedia content complements this work in order to help resolve ambiguity and to provide further contextual information. We provide two main innovations in this work: first, the novel combination of text and multimedia opinion mining tools; and second, the adaptation of NLP tools for opinion mining specific to the problems of social media.

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Published date: 10 December 2013

Additional Information: Funded by European Commission - FP7: A Decarbonisation Platform for Citizen Empowerment and Translating Collective Awareness into Behavioural Change (DECARBONET) (610829)

Venue - Dates: BCS SGAI Workshop on Social Media Analysis, 2013-12-10

Organisations: Web & Internet Science