Get Smart on Information-Sharing in Social Networks

Autor: Kalyani Emani, Vaishnavi Guduguntla, Xiaoqin Zhang, Gaurav Kulkarni, Pavan Kaparthi
Rok vydání: 2018
Předmět:
Zdroj: 2018 International Conference on Computational Science and Computational Intelligence (CSCI).
DOI: 10.1109/csci46756.2018.00242
Popis: Social Networks now become popular and powerful platforms for people to share information. Everyone may share their interested information with their connections, or send messages to their friends. However, sharing information costs both computational and communicational resources, in addition to personal time/attention of both the sender and the receiver. Decision-making regarding which piece of information should be shared with whom, thus is important to individuals and the whole network. In this work, we study the effects of different information-sharing strategies using a social network simulator. This paper describes how social network is modeled, and the various factors relevant to the sharing decisions. We propose six information sharing strategies, and performed simulation experiments to examine their influences on individuals and the whole social network.
Databáze: OpenAIRE