Analysing the Sentiment Expressed by Political Audiences on Twitter: The case of the 2017 UK General Election
dc.contributor.author | Plummer, M | |
dc.contributor.author | PALOMINO, MARCO | |
dc.contributor.author | masala, giovanni | |
dc.date.accessioned | 2019-05-19T14:31:37Z | |
dc.date.available | 2019-05-19T14:31:37Z | |
dc.date.issued | 2017-12-14 | |
dc.identifier.isbn | 978-1-5386-2652-8 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/14112 | |
dc.description.abstract |
A significant amount of research on the intersection of sentiment analysis and social media platforms has been published in the past few years. While previous studies have focused on methods to identify the polarity of online posts, little has been done in terms of using the impact of such posts to enhance the discovery and description of trends in real time. Here, we present a tool for the retrieval and analysis of microblogging posts in real time. We have gathered a large sample of tweets related to the 2017 UK General Election. We introduce a novel classification of the polarity of sentiments, considering the correlation between words, events and sentiments. | |
dc.format.extent | 1449-1454 | |
dc.language.iso | en | |
dc.publisher | IEEE | |
dc.subject | Information Retrieval Methods | |
dc.subject | Social Networks | |
dc.subject | Web Search and Information Extraction | |
dc.subject | Predictive Analytics | |
dc.title | Analysing the Sentiment Expressed by Political Audiences on Twitter: The case of the 2017 UK General Election | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000455029500257&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.date-start | 2017-12-14 | |
plymouth.date-finish | 2017-12-16 | |
plymouth.conference-name | 4th Annual Conference on Computational Science & Computational Intelligence (CSCI'17) | |
plymouth.publication-status | Published | |
plymouth.journal | ISBN: 1-60132-469-3 | |
dc.identifier.doi | 10.1109/CSCI.2017.253 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dc.publisher.place | Las Vegas, NV | |
dcterms.dateAccepted | 2017-11-06 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.1109/CSCI.2017.253 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2017-12-14 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |