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Systematic Measurement of Centralize...

Liu, Ling.

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Systematic Measurement of Centralized Online Reputation Systems.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Systematic Measurement of Centralized Online Reputation Systems./
Author:	Liu, Ling.
Description:	160 p.
Notes:	Source: Dissertation Abstracts International, Volume: 72-09, Section: B, page: .
Contained By:	Dissertation Abstracts International72-09B.
Subject:	Information Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3462731
ISBN:	9781124744988

Systematic Measurement of Centralized Online Reputation Systems.
Liu, Ling.

Systematic Measurement of Centralized Online Reputation Systems. - 160 p.

Source: Dissertation Abstracts International, Volume: 72-09, Section: B, page: .

Thesis (Ph.D.)--University of Durham (United Kingdom), 2011.

Background. Centralized online reputation systems, which collect users' opinions on products, transactions and events as reputation information then aggregate and publish it, have been widely adopted by Internet companies. These systems can help users build trust, reduce information asymmetry and filter information.

ISBN: 9781124744988Subjects--Topical Terms:

1030799
Information Technology.

Systematic Measurement of Centralized Online Reputation Systems.
LDR:02974nam 2200349 4500 001 1405042
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020 $a 9781124744988
035 $a (UMI)AAI3462731
035 $a AAI3462731
040 $a UMI $c UMI
100 1 $a Liu, Ling. $3 1036240
245 1 0 $a Systematic Measurement of Centralized Online Reputation Systems.
300 $a 160 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-09, Section: B, page: .
500 $a Advisers: Malcolm Munro; William W. Song.
502 $a Thesis (Ph.D.)--University of Durham (United Kingdom), 2011.
520 $a Background. Centralized online reputation systems, which collect users' opinions on products, transactions and events as reputation information then aggregate and publish it, have been widely adopted by Internet companies. These systems can help users build trust, reduce information asymmetry and filter information.
520 $a Aim. Much research in the area has focused on analyzing single type systems and the cross-type evaluation usually concentrates on one aspect of the system. This research proposes a systematic evaluation model (SERS) that can measure different types of reputation system.
520 $a Method. From system perspective, all reputation systems can be divided into five underlying components. Input refers to the collection of ratings and reviews; Processing is the aggregation of ratings. Output publishes the information. Feedback Loop is the collection of the feedback of the review, which can be seen as the 'review of the review'; Finally, Storage stores all the information. Therefore, based on each component's characteristics, a series of benchmark criteria can be defined and incorporated into the model.
520 $a Results. The SERS has defined 29 criteria, which can compare and measure different aspects of reputation systems. The model was theoretically assessed on its coverage of the successful factors of reputation systems and the technical dimensions of information systems. The model has also been empirically assessed by applying it to 15 commercial sites.
520 $a Conclusion. The results obtained indicated that the SERS model has identified most important characteristics that have been proposed by reputation systems literature. In addition the SERS has covered most dimensions of the two basic technical information system measurements: information quality and system quality. The empirical assessment has shown that the SERS can evaluate different types of reputation systems and is capable of identifying the weakness of current systems.
590 $a School code: 0585.
650 4 $a Information Technology. $3 1030799
650 4 $a Web Studies. $3 1026830
650 4 $a Computer Science. $3 626642
690 $a 0489
690 $a 0646
690 $a 0984
710 2 $a University of Durham (United Kingdom). $3 1293168
773 0 $t Dissertation Abstracts International $g 72-09B.
790 1 0 $a Munro, Malcolm, $e advisor
790 1 0 $a Song, William W., $e advisor
790 $a 0585
791 $a Ph.D.
792 $a 2011
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3462731