Title :
Modeling Community Influence in Social Networks with Markov Chains
Author :
Yuzhong Chen ; Jiawei Ying
Author_Institution :
Coll. of Math. & Comput. Sci., Fuzhou Univ., Fuzhou, China
Abstract :
Social network analysis has been one of the research focuses with the developing of social media services. Social influence also attracts ever-increasing attention and interests from both the sociology and the data mining scholars, but the research of influence is mainly limited in the user level, the community level influence is rarely involved. In this paper, we develop a novel model to analyze and evaluate the community level influence and help the decision maker to comprehend the disparity in influence of different communities. This paper also proposes a simple heuristic node-selection strategy considering the community influence to spread influence, and the experiments of the spread of influence through the social network datasets prove the rationality of the proposed community influence analysis model.
Keywords :
Markov processes; data mining; decision making; social networking (online); Markov chains; data mining scholars; decision maker; heuristic node selection strategy; modeling community influence; social media services; social network analysis; social network datasets; Analytical models; Communities; Educational institutions; Integrated circuit modeling; Markov processes; Peer-to-peer computing; Social network services; community level influence; influence maximization; influence spreading; social network;
Conference_Titel :
Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on
Conference_Location :
Fuzhou
Print_ISBN :
978-1-4799-2829-3
DOI :
10.1109/CLOUDCOM-ASIA.2013.77