Mitic, Peter;
(2017)
Standardised Reputation Measurement.
In: Yin, Hujun and Gao, Yang and Chen, Songcan and Wen, Yimin and Cai, Guoyong and Gu, Tianlong and Du, Junping and Tallon-Ballesteros, Antonio J and Zhang, Minling, (eds.)
Intelligent Data Engineering and Automated Learning – IDEAL 2017.
(pp. pp. 534-542).
Springer Publishing: Cham, Switzerland.
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Abstract
Well-defined formal definitions for sentiment and opinion are extended to incorporate the necessary elements to provide a formal quantitative definition of reputation. This definition takes the form of a time-based index, in which each element is a function of a collection of opinions mined during a given time period. The resulting formal definition is validated against informal notions of reputation. Practical aspects of data procurement to support such a reputation index are discussed. The assumption that all mined opinions comprise a complete set is questioned. A case is made that unexpressed positive sentiment exists, and can be quantified.
Type: | Proceedings paper |
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Title: | Standardised Reputation Measurement |
Event: | International Conference on Intelligent Data Engineering and Automated Learning: IDEAL 2017 |
ISBN-13: | 978-3-319-68934-0 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/978-3-319-68935-7_58 |
Publisher version: | https://doi.org/10.1007/978-3-319-68935-7_58 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use please refer to the publisher's terms and conditions. |
Keywords: | Reputation; Reputation index; Reputation definition; Opinion; Unexpressed positive sentiment |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10179251 |



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