Consumption experience model and identification based on IWOM and emotional computing
Consumer experience types were conducted with fuzzy calculation and type classification by excavating online comment information of e-commerce platform. Based on theoretical framework of five-dimensional system analysis, the work determined two dimensions of experience value and emotion to establish...
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| Veröffentlicht in: | Cluster computing 2018-03, Vol.21 (1), p.1023-1031 |
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| container_title | Cluster computing |
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| creator | Han, Yanqing Lei, Yuyan Chen, Guanju |
| description | Consumer experience types were conducted with fuzzy calculation and type classification by excavating online comment information of e-commerce platform. Based on theoretical framework of five-dimensional system analysis, the work determined two dimensions of experience value and emotion to establish consumer experience classification model. Thereinto, the experience value was determined by fuzzy reasoning theory, with antecedent of practical and hedonic values. Through online collection of IWOM from different phone brands, a corpus was established based on fuzzy words to achieve identification of consumers using different brands, providing marketing advice for enterprise. |
| doi_str_mv | 10.1007/s10586-017-1017-y |
| format | Article |
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Through online collection of IWOM from different phone brands, a corpus was established based on fuzzy words to achieve identification of consumers using different brands, providing marketing advice for enterprise.</description><subject>Brand identification</subject><subject>Brand image</subject><subject>Brand loyalty</subject><subject>Classification</subject><subject>Computer Communication Networks</subject><subject>Computer Science</subject><subject>Consumer behavior</subject><subject>Consumers</subject><subject>Consumption</subject><subject>Customer satisfaction</subject><subject>Decision making</subject><subject>Emotions</subject><subject>Fuzzy logic</subject><subject>Fuzzy sets</subject><subject>Internet</subject><subject>Marketing</subject><subject>Natural language</subject><subject>Operating Systems</subject><subject>Participation</subject><subject>Processor Architectures</subject><subject>Psychology</subject><subject>Semantics</subject><subject>Systems analysis</subject><subject>Two dimensional analysis</subject><issn>1386-7857</issn><issn>1573-7543</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kFFLwzAUhYMoOKc_wLeCz9XcpFnaRxnqBpO9OHwMaXI7OtamJi24f2-6Cj75cu-F853L4RByD_QRKJVPAajIFykFmcI4ThdkBkLyVIqMX8abR1XmQl6TmxAOlNJCsmJGdkvXhqHp-tq1CX536GtsDSaNs3hMdGuT2mLb11Vt9JkpdUCbxGP9uX0_A9i4UdHHxLimG_q63d-Sq0ofA9797jnZvb58LFfpZvu2Xj5vUhPj9KktKauQGrvQFEBbaqCQsuKZwAILBpwDoNXVIgeM2XnOGIiyZJAxZHmV8Tl5mP523n0NGHp1cIOPUYJiBeQMpMhlpGCijHcheKxU5-tG-5MCqsb21NSeisWpsT11ih42eUJk2z36v8__m34AIkNy0Q</recordid><startdate>20180301</startdate><enddate>20180301</enddate><creator>Han, Yanqing</creator><creator>Lei, Yuyan</creator><creator>Chen, Guanju</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</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>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0001-8756-3305</orcidid></search><sort><creationdate>20180301</creationdate><title>Consumption experience model and identification based on IWOM and emotional computing</title><author>Han, Yanqing ; 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| ispartof | Cluster computing, 2018-03, Vol.21 (1), p.1023-1031 |
| issn | 1386-7857 1573-7543 |
| language | eng |
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| source | SpringerLink Journals - AutoHoldings; ProQuest Central |
| subjects | Brand identification Brand image Brand loyalty Classification Computer Communication Networks Computer Science Consumer behavior Consumers Consumption Customer satisfaction Decision making Emotions Fuzzy logic Fuzzy sets Internet Marketing Natural language Operating Systems Participation Processor Architectures Psychology Semantics Systems analysis Two dimensional analysis |
| title | Consumption experience model and identification based on IWOM and emotional computing |
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