The University of Southampton
University of Southampton Institutional Repository

Multimodal Sentiment Analysis of Social Media

Multimodal Sentiment Analysis of Social Media
Multimodal Sentiment Analysis of Social Media
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.
Maynard, Diana
08c91134-4de7-403f-aff7-c57daae2c01a
Dupplaw, David
c563ca2b-756a-4d3f-bf99-4f60bb2be1ce
Hare, Jonathon
65ba2cda-eaaf-4767-a325-cd845504e5a9
Maynard, Diana
08c91134-4de7-403f-aff7-c57daae2c01a
Dupplaw, David
c563ca2b-756a-4d3f-bf99-4f60bb2be1ce
Hare, Jonathon
65ba2cda-eaaf-4767-a325-cd845504e5a9

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)

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 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.

PDF arcomem.pdf - Version of Record
Download (303kB)

More information

Published date: 10 December 2013
Venue - Dates: BCS SGAI Workshop on Social Media Analysis, 2013-12-10
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 360546
URI: http://eprints.soton.ac.uk/id/eprint/360546
PURE UUID: 70ee4051-399c-4a61-a9b5-19215e28ff21
ORCID for Jonathon Hare: ORCID iD orcid.org/0000-0003-2921-4283

Catalogue record

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

Export record

Contributors

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

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×