Construction of the Information Dissemination Model and Calculation of User Influence Based on Attenuation Coefficient

Abstract

Users’ online activities serve as a mirror, reflecting their unique personas, affiliations, interests, and hobbies within the real world. Network information dissemination is inherently targeted, as users actively seek information to facilitate precise and swift communication. Delving into the nuances of information propagation on the Internet holds immense potential for facilitating commercial endeavors such as targeted advertising, personalized product recommendations, and insightful consumer behavior analyses. Recognizing that the intensity of information transmission diminishes with the proliferation of competing messages, increased transmission distances, and the passage of time, this paper draws inspiration from the concept of heat attenuation to formulate an innovative information propagation model. This model simulates the “heat index” of each node in the transmission process, thereby capturing the dynamic nature of information flow. Extensive experiments, bolstered by comparative analyses of multiple datasets and relevant algorithms, validate the correctness, feasibility, and efficiency of our proposed algorithm. Notably, our approach demonstrates remarkable accuracy and stability, underscoring its potential for real-world applications.