1. Product information diffusion in a social network
- Author
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Manman Luo, Robert J. Boncella, and Ling Zhang
- Subjects
Social network ,Computer science ,business.industry ,05 social sciences ,Economics, Econometrics and Finance (miscellaneous) ,Diffusion network ,02 engineering and technology ,Data science ,law.invention ,Human-Computer Interaction ,Information behavior ,Range (mathematics) ,PageRank ,law ,020204 information systems ,0502 economics and business ,Node (computer science) ,0202 electrical engineering, electronic engineering, information engineering ,050211 marketing ,Product (category theory) ,Diffusion (business) ,business - Abstract
There is a need to understand how to: spread product information to maximum range, identifying influential users, and analyze how they are intrinsically connected in a social network. In this paper, we collected tweets of Huawei Mate 9 to analyze users’ information behavior such as tweeting, forwarding, and commenting on tweets. We applied independent cascade model to this empirical Twitter diffusion network, and found it is proper to fit to the product information diffusion process. Using its network structure and PageRank measurement, we can identify influential nodes, and interpret the intrinsic connection between these influential nodes. Further, it is significant to consider the node’s background, such as interest, occupation, and country when identifying influential nodes. And it is discussed that the tweet content related to novel technology may attract more participation in ordinary users.
- Published
- 2018
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