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SentiCircles: a platform for contextual and conceptual sentiment analysis

SentiCircles: a platform for contextual and conceptual sentiment analysis
SentiCircles: a platform for contextual and conceptual sentiment analysis
Sentiment analysis over social streams offers governments and organisations a fast and effective way to monitor the publics’ feelings towards policies, brands, business, etc. In this paper we present SentiCircles, a platform that captures feedback from social media conversations and applies contextual and conceptual sentiment analysis models to extract and summarise sentiment from these conversations. It provides a novel sentiment navigation design where contextual sentiment is captured and presented at term/entity level, enabling a better alignment of positive and negative sentiment to the nature of the public debate.
Saif, Hassan
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Bashevoy, Maxim
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Taylor, Stephen
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Fernandez, Miriam
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Alani, Harith
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Saif, Hassan
d07f3478-5b8a-4c52-bd8c-176df3fd65a0
Bashevoy, Maxim
1b03d4b1-2f0f-41cb-b6d5-064d7f0a1f69
Taylor, Stephen
9ee68548-2096-4d91-a122-bbde65f91efb
Fernandez, Miriam
ba0ba09f-fe79-413e-bf40-4c6dd0a9c6b8
Alani, Harith
70cdbdce-1494-44c2-9dae-65d82bf7e991

Saif, Hassan, Bashevoy, Maxim, Taylor, Stephen, Fernandez, Miriam and Alani, Harith (2016) SentiCircles: a platform for contextual and conceptual sentiment analysis. ESWC2016: European Semantic Web Conference, Crete, Greece. 29 May - 02 Jun 2016. 5 pp . (doi:10.1007/978-3-319-47602-5_28).

Record type: Conference or Workshop Item (Other)

Abstract

Sentiment analysis over social streams offers governments and organisations a fast and effective way to monitor the publics’ feelings towards policies, brands, business, etc. In this paper we present SentiCircles, a platform that captures feedback from social media conversations and applies contextual and conceptual sentiment analysis models to extract and summarise sentiment from these conversations. It provides a novel sentiment navigation design where contextual sentiment is captured and presented at term/entity level, enabling a better alignment of positive and negative sentiment to the nature of the public debate.

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More information

Accepted/In Press date: 25 April 2016
e-pub ahead of print date: 20 October 2016
Published date: 2016
Additional Information: Paper given in Demonstrations Track given at 13th ESWC 2016
Venue - Dates: ESWC2016: European Semantic Web Conference, Crete, Greece, 2016-05-29 - 2016-06-02
Organisations: IT Innovation

Identifiers

Local EPrints ID: 393451
URI: http://eprints.soton.ac.uk/id/eprint/393451
PURE UUID: c868623f-9634-43ee-b868-646e7ca48189
ORCID for Maxim Bashevoy: ORCID iD orcid.org/0000-0003-2068-9047
ORCID for Stephen Taylor: ORCID iD orcid.org/0000-0002-9937-1762

Catalogue record

Date deposited: 26 Apr 2016 11:19
Last modified: 15 Mar 2024 03:24

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Contributors

Author: Hassan Saif
Author: Maxim Bashevoy ORCID iD
Author: Stephen Taylor ORCID iD
Author: Miriam Fernandez
Author: Harith Alani

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