Predicting the Popularity of Online Content by Modeling the Social Influence and Homophily Features

Abstract

Predicting the popularity of online content on social network can bring considerable economic benefits to companies and marketers, and it has wide application in viral marketing, content recommendation, early warning of social unrest, etc. The diffusion process of online contents is often a complex combination of both social influence and homophily; however, existing works either only consider the social influence or homophily of early infected users and fail to model the joint effect of social influence and homophily when predicting future popularity. In this study, we aim to develop a framework to unify the social influence and homophily in popularity prediction. We use an unsupervised graph neural network framework to model nondirectional social homophily and integrate the attention mechanism with the graph neural network framework to learn the directional and heterogeneous social relationship for generating social influence representation. On the other hand, existing research studies often overlook the social group characteristics of early infected users, and we try to divide users into different social groups based on user interest and learn the social group representation from clusters. We integrate the social influence, homophily, and social group representation of early infected users to make popularity predictions. Experiments on real datasets show that the proposed method significantly improves the prediction accuracy compared with the latest methods, which confirms the importance of joint model social influence and homophily and shows that social group characteristic is an important predictor in the popularity prediction task.

“I think exactly the same”—trust in SMIs and online purchase intention: a moderation mediation analysis using PLS-SEM

“…The term "homophily" also known as "similarity," refers to "the extent to which persons with whom one interacts are similar in beliefs, education, social standing, values, attitudes and the like" (Eyal and Rubin, 2003;Gilly et al, 1998;Lazarsfeld and Merton, 1954). Homophily is more prevalent in the communication discipline, although it is a comparatively recent phenomenon in the marketing field, especially appearing in social contexts such as social commerce, netizens, bloggers and online content (Khanam et al, 2023a, b;Phua et al, 2017;Sakib et al, 2020;Shang et al, 2022;Sokolova and Kefi, 2020;Wang et al, 2008).…”

“…Homophily has been used to explain electronic word of mouth (eWOM), the experiences provided by websites, online content, the development of brands and athlete influencer credibility (Filieri et al, 2023;Leonhardt et al, 2020;Muda and Hamzah, 2021;Park et al, 2021;Phua et al, 2017;Shang et al, 2022;Su et al, 2023) and how different dimensions of homophily affect a person's popularity (Ladhari et al, 2020). According to McCroskey et al (1975), there exist four dimensions of homophily, namely attitude, background, morality and appearance.…”

A Predictive Paradigm for Event Popularity in Event-Based Social Networks

“…Shang et al [20] integrated social influence with homophily into a model to predict online content popularity. Dou et al [21] also predicted online content popularity with rich information.…”