A new method for evaluating tour online review based on grey 2-tuple linguistic
Purpose – Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non-structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are im...
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| Veröffentlicht in: | Kybernetes 2014-01, Vol.43 (3/4), p.601-613 |
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| container_title | Kybernetes |
| container_volume | 43 |
| creator | Mi, Chuanmin Shan, Xiaofei Qiang, Yuan Stephanie, Yosa Chen, Ye |
| description | Purpose
– Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non-structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2-tuple linguistic.
Design/methodology/approach
– The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2-tuple linguistic evaluation model for tour online review is proposed.
Findings
– Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2-tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account.
Research limitations/implications
– Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future.
Practical implications
– Grey 2-tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world.
Originality/value
– A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed. |
| doi_str_mv | 10.1108/K-06-2013-0123 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_emera</sourceid><recordid>TN_cdi_emerald_primary_10_1108_K-06-2013-0123</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3257980721</sourcerecordid><originalsourceid>FETCH-LOGICAL-c338t-9564a8cff8e9c79d4d6ce0740f92a048a154dc7fedddb5851a5a6e00a7d4252b3</originalsourceid><addsrcrecordid>eNpl0U1LAzEQBuAgCtaPq-eAFy-pk2SzyR5L8YsWelHwFtLNbN2y3a3JbqX_3pR6UU-B4Zlh8g4hNxzGnIO5nzHImQAuGXAhT8iIa2WYNkaekhHI3LCsEO_n5CLGNSSSCxiRxYS2-EU32H90nlZdoLhzzeD6ul3RvhsC7dqmbpEG3NUJLl1En2p0FXBPBeuHbYM0idVQx74ur8hZ5ZqI1z_vJXl7fHidPrP54ullOpmzUkrTs0LlmTNlVRksSl34zOclgs6gKoSDzDiuMl_qCr33S2UUd8rlCOC0z4QSS3lJ7o5zt6H7HDD2dlPHEpvGtdgN0XIloSiE1iLR2z90nf7Vpu2S4qAKrbRManxUZehiDFjZbag3LuwtB3vI184s5PaQrz3kmxrYsQE3GFzj__tf95Df1NZ6Eg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1510597573</pqid></control><display><type>article</type><title>A new method for evaluating tour online review based on grey 2-tuple linguistic</title><source>Emerald Journals</source><creator>Mi, Chuanmin ; Shan, Xiaofei ; Qiang, Yuan ; Stephanie, Yosa ; Chen, Ye</creator><contributor>Sonja Sibila Lebe, Prof Matjaž Mulej, Dr</contributor><creatorcontrib>Mi, Chuanmin ; Shan, Xiaofei ; Qiang, Yuan ; Stephanie, Yosa ; Chen, Ye ; Sonja Sibila Lebe, Prof Matjaž Mulej, Dr</creatorcontrib><description>Purpose
– Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non-structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2-tuple linguistic.
Design/methodology/approach
– The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2-tuple linguistic evaluation model for tour online review is proposed.
Findings
– Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2-tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account.
Research limitations/implications
– Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future.
Practical implications
– Grey 2-tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world.
Originality/value
– A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed.</description><identifier>ISSN: 0368-492X</identifier><identifier>EISSN: 1758-7883</identifier><identifier>DOI: 10.1108/K-06-2013-0123</identifier><identifier>CODEN: KBNTA3</identifier><language>eng</language><publisher>London: Emerald Group Publishing Limited</publisher><subject>Decision making ; Design engineering ; Information & knowledge management ; Information systems ; Internet resources ; Linguistics ; Links ; Networks ; On-line systems ; Online ; Social networks ; Social responsibility ; Teachers ; Tours ; Web sites</subject><ispartof>Kybernetes, 2014-01, Vol.43 (3/4), p.601-613</ispartof><rights>Emerald Group Publishing Limited</rights><rights>Copyright Emerald Group Publishing Limited 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c338t-9564a8cff8e9c79d4d6ce0740f92a048a154dc7fedddb5851a5a6e00a7d4252b3</citedby><cites>FETCH-LOGICAL-c338t-9564a8cff8e9c79d4d6ce0740f92a048a154dc7fedddb5851a5a6e00a7d4252b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/K-06-2013-0123/full/pdf$$EPDF$$P50$$Gemerald$$H</linktopdf><linktohtml>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/K-06-2013-0123/full/html$$EHTML$$P50$$Gemerald$$H</linktohtml><link.rule.ids>314,778,782,964,11618,27907,27908,52669,52672</link.rule.ids></links><search><contributor>Sonja Sibila Lebe, Prof Matjaž Mulej, Dr</contributor><creatorcontrib>Mi, Chuanmin</creatorcontrib><creatorcontrib>Shan, Xiaofei</creatorcontrib><creatorcontrib>Qiang, Yuan</creatorcontrib><creatorcontrib>Stephanie, Yosa</creatorcontrib><creatorcontrib>Chen, Ye</creatorcontrib><title>A new method for evaluating tour online review based on grey 2-tuple linguistic</title><title>Kybernetes</title><description>Purpose
– Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non-structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2-tuple linguistic.
Design/methodology/approach
– The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2-tuple linguistic evaluation model for tour online review is proposed.
Findings
– Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2-tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account.
Research limitations/implications
– Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future.
Practical implications
– Grey 2-tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world.
Originality/value
– A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed.</description><subject>Decision making</subject><subject>Design engineering</subject><subject>Information & knowledge management</subject><subject>Information systems</subject><subject>Internet resources</subject><subject>Linguistics</subject><subject>Links</subject><subject>Networks</subject><subject>On-line systems</subject><subject>Online</subject><subject>Social networks</subject><subject>Social responsibility</subject><subject>Teachers</subject><subject>Tours</subject><subject>Web sites</subject><issn>0368-492X</issn><issn>1758-7883</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpl0U1LAzEQBuAgCtaPq-eAFy-pk2SzyR5L8YsWelHwFtLNbN2y3a3JbqX_3pR6UU-B4Zlh8g4hNxzGnIO5nzHImQAuGXAhT8iIa2WYNkaekhHI3LCsEO_n5CLGNSSSCxiRxYS2-EU32H90nlZdoLhzzeD6ul3RvhsC7dqmbpEG3NUJLl1En2p0FXBPBeuHbYM0idVQx74ur8hZ5ZqI1z_vJXl7fHidPrP54ullOpmzUkrTs0LlmTNlVRksSl34zOclgs6gKoSDzDiuMl_qCr33S2UUd8rlCOC0z4QSS3lJ7o5zt6H7HDD2dlPHEpvGtdgN0XIloSiE1iLR2z90nf7Vpu2S4qAKrbRManxUZehiDFjZbag3LuwtB3vI184s5PaQrz3kmxrYsQE3GFzj__tf95Df1NZ6Eg</recordid><startdate>20140101</startdate><enddate>20140101</enddate><creator>Mi, Chuanmin</creator><creator>Shan, Xiaofei</creator><creator>Qiang, Yuan</creator><creator>Stephanie, Yosa</creator><creator>Chen, Ye</creator><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>7XB</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20140101</creationdate><title>A new method for evaluating tour online review based on grey 2-tuple linguistic</title><author>Mi, Chuanmin ; Shan, Xiaofei ; Qiang, Yuan ; Stephanie, Yosa ; Chen, Ye</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c338t-9564a8cff8e9c79d4d6ce0740f92a048a154dc7fedddb5851a5a6e00a7d4252b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Decision making</topic><topic>Design engineering</topic><topic>Information & knowledge management</topic><topic>Information systems</topic><topic>Internet resources</topic><topic>Linguistics</topic><topic>Links</topic><topic>Networks</topic><topic>On-line systems</topic><topic>Online</topic><topic>Social networks</topic><topic>Social responsibility</topic><topic>Teachers</topic><topic>Tours</topic><topic>Web sites</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mi, Chuanmin</creatorcontrib><creatorcontrib>Shan, Xiaofei</creatorcontrib><creatorcontrib>Qiang, Yuan</creatorcontrib><creatorcontrib>Stephanie, Yosa</creatorcontrib><creatorcontrib>Chen, Ye</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Kybernetes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mi, Chuanmin</au><au>Shan, Xiaofei</au><au>Qiang, Yuan</au><au>Stephanie, Yosa</au><au>Chen, Ye</au><au>Sonja Sibila Lebe, Prof Matjaž Mulej, Dr</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new method for evaluating tour online review based on grey 2-tuple linguistic</atitle><jtitle>Kybernetes</jtitle><date>2014-01-01</date><risdate>2014</risdate><volume>43</volume><issue>3/4</issue><spage>601</spage><epage>613</epage><pages>601-613</pages><issn>0368-492X</issn><eissn>1758-7883</eissn><coden>KBNTA3</coden><abstract>Purpose
– Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non-structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2-tuple linguistic.
Design/methodology/approach
– The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2-tuple linguistic evaluation model for tour online review is proposed.
Findings
– Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2-tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account.
Research limitations/implications
– Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future.
Practical implications
– Grey 2-tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world.
Originality/value
– A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed.</abstract><cop>London</cop><pub>Emerald Group Publishing Limited</pub><doi>10.1108/K-06-2013-0123</doi><tpages>13</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0368-492X |
| ispartof | Kybernetes, 2014-01, Vol.43 (3/4), p.601-613 |
| issn | 0368-492X 1758-7883 |
| language | eng |
| recordid | cdi_emerald_primary_10_1108_K-06-2013-0123 |
| source | Emerald Journals |
| subjects | Decision making Design engineering Information & knowledge management Information systems Internet resources Linguistics Links Networks On-line systems Online Social networks Social responsibility Teachers Tours Web sites |
| title | A new method for evaluating tour online review based on grey 2-tuple linguistic |
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