Saif, Hassan; Bashevoy, Maxim; Taylor, Steve; Fernández, Miriam and Alani, Harith
(2016).
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| URL: | http://2016.eswc-conferences.org/sites/default/fil... |
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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.
| Item Type: | Conference or Workshop Item |
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| Keywords: | social media; sentiment analysis |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Research Group: | Centre for Research in Computing (CRC) |
| Related URLs: | |
| Item ID: | 48480 |
| Depositing User: | Kay Dave |
| Date Deposited: | 20 Feb 2017 16:22 |
| Last Modified: | 07 Dec 2018 13:32 |
| URI: | http://oro.open.ac.uk/id/eprint/48480 |
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