Research Methods on Recognizing Potential Opinion Leaders of Hot Event Based on Social Network

Abstract

Recognizing the "opinion leaders" in advance is a new requirement in the context of social network. "From back to front" approaches do not conform to the transmission and evolution of development process of hot events. To address this problem, this paper proposes the concept of "potential opinion leaders", who is a user will become opinion leaders before the common event becoming hot. Our approach intuitively starts from the real development process of hot events, takes advantage of the "from front to back" dynamic research mode according to the propagation characteristics of hot events, and uses fan's number and identity tags as the screening criteria. We then design the analysis algorithm to recognize the "potential opinion leaders".The experimental result is compared with the traditional opinion leaders. It demonstrates that the recognition method by using "potential opinion leaders" is simpler, and guiding significance for network early warning is stronger.