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Towards understanding cross-cultural crowd sentiment using social media

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dc.contributor.authorWang Y.en_US
dc.contributor.authorSiriaraya P.en_US
dc.contributor.authorMohd Pozi M.S.en_US
dc.contributor.authorKawai Y.en_US
dc.contributor.authorJatowt A.en_US
dc.contributor.authorid56242936500en_US
dc.contributor.authorid47562025200en_US
dc.contributor.authorid57219746822en_US
dc.contributor.authorid8902658900en_US
dc.contributor.authorid14826985000en_US
dc.date.accessioned2023-05-29T06:57:03Z
dc.date.available2023-05-29T06:57:03Z
dc.date.issued2018
dc.descriptionData mining; Sentiment analysis; Cross-cultural differences; Cross-cultural study; Geographical area; Network-based approach; Similar but sentimentally different; Social media; Social networking (online)en_US
dc.description.abstractSocial media such as Twitter has been frequently used for expressing personal opinions and sentiments at different places. In this paper, we propose a novel crowd sentiment analysis for fostering cross-cultural studies. In particular, we aim to find similar meanings but different sentiments between tweets collected over geographical areas. For this, we detect sentiments and topics of each tweet by applying neural network based approaches, and we assign sentiments to each topic based on the sentiments of the corresponding tweets. This permits finding cross-cultural patterns by computing topic and sentiment correspondence. The proposed methods enable to analyze tweets from diverse geographical areas sentimentally in order to explore cross-cultural differences. � Springer International Publishing AG, part of Springer Nature 2018.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-3-319-78105-1_8
dc.identifier.epage73
dc.identifier.scopus2-s2.0-85044418132
dc.identifier.spage67
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85044418132&doi=10.1007%2f978-3-319-78105-1_8&partnerID=40&md5=65e53b3ce918b7cf9a744e3d031ad720
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24213
dc.identifier.volume10766 LNCS
dc.publisherSpringer Verlagen_US
dc.sourceScopus
dc.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.titleTowards understanding cross-cultural crowd sentiment using social mediaen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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