In this paper, we are interested in answering the following research question: Is it possible to form effective groups in virtual communities by exploiting trust information without significant overhead, similarly to real user communities? In order to answer this question, instead of adopting the largely used approach of exploiting the opinions provided by all the users of the community (called global reputation), we propose to use a particular form of reputation, called local reputation. We also propose an algorithm for group formation able to implement the proposed procedure to form effective groups in virtual communities. Another interesting question is how to measure the effectiveness of groups in virtual communities. To this aim we introduce the Gk index in a measure of the effectiveness of the group formation. We tested our algorithm by realizing some experimental trials on real data from the real world EPINIONS and CIAO communities, showing the significant advantages of our procedure w.r.t. another prominent approach based on traditional global reputation.
Evaluating group formation in virtual communities / Fortino, G.; Liotta, A.; Messina, F.; Rosaci, D.; Sarne, G. M. L.. - In: IEEE/CAA JOURNAL OF AUTOMATICA SINICA. - ISSN 2329-9266. - 7:4(2020), pp. 1003-1015. [10.1109/JAS.2020.1003237]
Evaluating group formation in virtual communities
Rosaci D.;Sarne G. M. L.
2020-01-01
Abstract
In this paper, we are interested in answering the following research question: Is it possible to form effective groups in virtual communities by exploiting trust information without significant overhead, similarly to real user communities? In order to answer this question, instead of adopting the largely used approach of exploiting the opinions provided by all the users of the community (called global reputation), we propose to use a particular form of reputation, called local reputation. We also propose an algorithm for group formation able to implement the proposed procedure to form effective groups in virtual communities. Another interesting question is how to measure the effectiveness of groups in virtual communities. To this aim we introduce the Gk index in a measure of the effectiveness of the group formation. We tested our algorithm by realizing some experimental trials on real data from the real world EPINIONS and CIAO communities, showing the significant advantages of our procedure w.r.t. another prominent approach based on traditional global reputation.File | Dimensione | Formato | |
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