DocumentCode :
1776905
Title :
Decision making improvement in social marketing strategy through dependent multi-dimensional opinion formation
Author :
Salehi, Sarvenaz ; Taghiyareh, Fattaneh
Author_Institution :
Electr. & Comput. Eng. (ECE, Univ. of Tehran, Tehran, Iran
fYear :
2014
fDate :
29-30 Oct. 2014
Firstpage :
111
Lastpage :
116
Abstract :
One of the most interesting topics in social network research is opinion formation. In this paper we have introduced a new dependent multi-dimensional opinion formation method. This method models agents with several dependent opinions so that modifying the agent´s opinion about one issue can affect its opinion about another issue. Agents share their opinion with agents which have trusted them. A directed graph is used for modeling this trust network. It can be modified based on the opinion sharing between agents. By applying this algorithm in the marketing area, Predicted opinions could be used for creating management reports to facilitate strategy definition and decision making. The results of applying this method on the “Epinion” dataset show that agent´s opinions converge to a stable state and a set of clusters have been formed in the community. Prediction of agent´s opinion can be used for identifying appropriate products and customers and defining right marketing strategy.
Keywords :
decision making; directed graphs; marketing; multi-agent systems; social networking (online); Epinion; decision making; dependent multidimensional opinion formation; directed graph; social marketing strategy; social network; trust network; Classification algorithms; Communities; Context; Correlation; Decision making; Filtering; Vectors; Opinion formation; agent; decision making; marketing strategy; recommender system; trust;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Knowledge Engineering (ICCKE), 2014 4th International eConference on
Conference_Location :
Mashhad
Print_ISBN :
978-1-4799-5486-5
Type :
conf
DOI :
10.1109/ICCKE.2014.6993353
Filename :
6993353
Link To Document :
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