Analyzing Information Dissemination on Social Networks
Zhang Ling1(), Luo Manman1, Zhu Lijun2
1(School of Management, Wuhan University of Science and Technology, Wuhan 430081, China) 2(Institute of Scientific and Technical Information of China, Beijing 100038, China)
[Objective] This study analyzes the dissemination of marketing information on social network systems, aiming to identify the most influential nodes. [Methods] We collected Twitter data on Huawei Mate 9 smartphone to analyze users’ information behaviors like tweeting, retweeting and commenting. First, the network topology was described as topology structure diagram; Second, we examined scales of the network; Finally, we used independent cascade model (ICM) to simulate information dissemination. [Results] We found that initial active nodes selection based on the new measurements performed well. [Limitations] The parameters of ICM could be optimized. [Conclusions] The enterprises should pay attention to both official and accidental nodes to retrieve feedback from the market.
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