Developing a Theory of Diagnosticity for Online Reviews
Diagnosticity of a given online review is defined as the extent to which it helps users make informed purchase decisions. Users’ perception of review diagnosticity can be associated with five factors, namely, review rating, review depth, review readability, reviewer profile and product type. Review...
| मुख्य लेखकों: | , |
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| अन्य लेखक: | |
| स्वरूप: | Conference Paper |
| भाषा: | English |
| प्रकाशित: |
2017
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| विषय: | |
| ऑनलाइन पहुंच: | https://hdl.handle.net/10356/85829 http://hdl.handle.net/10220/43861 http://www.iaeng.org/publication/IMECS2014/IMECS2014_pp477-482.pdf |
| _version_ | 1826116907090051072 |
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| author | Chua, Alton Yeow Kuan Banerjee, Snehasish |
| author2 | Wee Kim Wee School of Communication and Information |
| author_facet | Wee Kim Wee School of Communication and Information Chua, Alton Yeow Kuan Banerjee, Snehasish |
| author_sort | Chua, Alton Yeow Kuan |
| collection | NTU |
| description | Diagnosticity of a given online review is defined as the extent to which it helps users make informed purchase decisions. Users’ perception of review diagnosticity can be associated with five factors, namely, review rating, review depth, review readability, reviewer profile and product type. Review rating refers to the numerical valence of reviews on a scale of one to five. Review depth refers to the quantity of textual arguments provided in reviews. Review readability measures the extent to which the textual arguments are comprehensible. Reviewer profile indicates the past track record of users who contribute reviews. Product type includes experience products and search products. Few studies hitherto have analyzed review diagnosticity taking into account all these factors concurrently. Hence, this paper attempts to augment prior research by developing a theory of diagnosticity for online reviews. The theory posits that review diagnosticity is shaped by the interplay among review rating, review depth, review readability and reviewer profile albeit differently between experience products and search products. |
| first_indexed | 2024-10-01T04:19:05Z |
| format | Conference Paper |
| id | ntu-10356/85829 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:19:05Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | ntu-10356/858292019-12-06T16:10:56Z Developing a Theory of Diagnosticity for Online Reviews Chua, Alton Yeow Kuan Banerjee, Snehasish Wee Kim Wee School of Communication and Information Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS) 2014 Review Diagnosticity Online Reviews Diagnosticity of a given online review is defined as the extent to which it helps users make informed purchase decisions. Users’ perception of review diagnosticity can be associated with five factors, namely, review rating, review depth, review readability, reviewer profile and product type. Review rating refers to the numerical valence of reviews on a scale of one to five. Review depth refers to the quantity of textual arguments provided in reviews. Review readability measures the extent to which the textual arguments are comprehensible. Reviewer profile indicates the past track record of users who contribute reviews. Product type includes experience products and search products. Few studies hitherto have analyzed review diagnosticity taking into account all these factors concurrently. Hence, this paper attempts to augment prior research by developing a theory of diagnosticity for online reviews. The theory posits that review diagnosticity is shaped by the interplay among review rating, review depth, review readability and reviewer profile albeit differently between experience products and search products. Published version 2017-10-12T05:03:18Z 2019-12-06T16:10:56Z 2017-10-12T05:03:18Z 2019-12-06T16:10:56Z 2014 Conference Paper Chua, A. Y. K., & Banerjee, S. (2014). Developing a theory of diagnosticity for online reviews. Proceedings of The International MultiConference of Engineers and Computer Scientists (IMECS) 2014, 477-482. https://hdl.handle.net/10356/85829 http://hdl.handle.net/10220/43861 http://www.iaeng.org/publication/IMECS2014/IMECS2014_pp477-482.pdf en © 2014 International Association of Engineers (IAENG). This paper was published in Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS) 2014 and is made available as an electronic reprint (preprint) with permission of International Association of Engineers (IAENG). The published version is available at: [http://www.iaeng.org/publication/IMECS2014/IMECS2014_pp477-482.pdf]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 6 p. application/pdf |
| spellingShingle | Review Diagnosticity Online Reviews Chua, Alton Yeow Kuan Banerjee, Snehasish Developing a Theory of Diagnosticity for Online Reviews |
| title | Developing a Theory of Diagnosticity for Online Reviews |
| title_full | Developing a Theory of Diagnosticity for Online Reviews |
| title_fullStr | Developing a Theory of Diagnosticity for Online Reviews |
| title_full_unstemmed | Developing a Theory of Diagnosticity for Online Reviews |
| title_short | Developing a Theory of Diagnosticity for Online Reviews |
| title_sort | developing a theory of diagnosticity for online reviews |
| topic | Review Diagnosticity Online Reviews |
| url | https://hdl.handle.net/10356/85829 http://hdl.handle.net/10220/43861 http://www.iaeng.org/publication/IMECS2014/IMECS2014_pp477-482.pdf |
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