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Multimodal Sentiment Analysis of Social Media

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

Record type: Conference or Workshop Item (Paper)


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 mater- ial for inclusion in an archive of social media for preserving community memories, moving towards structured preservation around semantic cat- egories. 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
Venue - Dates: BCS SGAI Workshop on Social Media Analysis, 2013-12-10
Organisations: Web & Internet Science


Local EPrints ID: 360546
PURE UUID: 70ee4051-399c-4a61-a9b5-19215e28ff21
ORCID for Jonathon Hare: ORCID iD

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Date deposited: 12 Dec 2013 13:22
Last modified: 18 Jul 2017 03:11

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Author: Diana Maynard
Author: David Dupplaw
Author: Jonathon Hare ORCID iD

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