Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/119669
DC FieldValueLanguage
dc.contributor資管系-
dc.creator楊亨利zh_TW
dc.creatorYang, Heng-Lien_US
dc.creatorChao, August F.Y.en_US
dc.date2018-
dc.date.accessioned2018-08-28T02:40:31Z-
dc.date.available2018-08-28T02:40:31Z-
dc.date.issued2018-08-28T02:40:31Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/119669-
dc.description.abstractPurpose\r\nThe purpose of this paper is to propose sentiment annotation at sentence level to reduce information overloading while reading product/service reviews in the internet.\r\n\r\nDesign/methodology/approach\r\nThe keyword-based sentiment analysis is applied for highlighting review sentences. An experiment is conducted for demonstrating its effectiveness.\r\n\r\nFindings\r\nA prototype is built for highlighting tourism review sentences in Chinese with positive or negative sentiment polarity. An experiment results indicates that sentiment annotation can increase information quality and user’s intention to read tourism reviews.\r\n\r\nResearch limitations/implications\r\nThis study has made two major contributions: proposing the approach of adding sentiment annotation at sentence level of review texts for assisting decision-making; validating the relationships among the information quality constructs. However, in this study, sentiment analysis was conducted on a limited corpus; future research may try a larger corpus. Besides, the annotation system was built on the tourism data. Future studies might try to apply to other areas.\r\n\r\nPractical implications\r\nIf the proposed annotation systems become popular, both tourists and attraction providers would obtain benefits. In this era of smart tourism, tourists could browse through the huge amount of internet information more quickly. Attraction providers could understand what are the strengths and weaknesses of their facilities more easily. The application of this sentiment analysis is possible for other languages, especially for non-spaced languages.\r\n\r\nOriginality/value\r\nFacing large amounts of data, past researchers were engaged in automatically constructing a compact yet meaningful abstraction of the texts. However, users have different positions and purposes. This study proposes an alternative approach to add sentiment annotation at sentence level for assisting users.en_US
dc.format.extent489006 bytes-
dc.format.mimetypeapplication/pdf-
dc.relationOnline Information Review,VOLUME 42, ISSUE 5 , pp.579-594-
dc.subjectInformation quality; Sentiment analysis; Tourism; Chinese review analysis; Sentiment annotationen_US
dc.titleSentiment Annotations for Reviews: An Information Quality Perspectiveen_US
dc.typearticle-
dc.identifier.doi10.1108/OIR-04-2017-0114-
dc.doi.urihttps://doi.org/10.1108/OIR-04-2017-0114-
item.grantfulltextrestricted-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
Appears in Collections:期刊論文
Files in This Item:
File Description SizeFormat
42-5.pdf477.54 kBAdobe PDF2View/Open
Show simple item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.