Probabilistic reasoning system for social influence analysis in online social networks
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ORIGINAL ARTICLE
Probabilistic reasoning system for social influence analysis in online social networks Lea Vega1 · Andres Mendez‑Vazquez1 · Armando López‑Cuevas2 Received: 16 December 2019 / Revised: 26 August 2020 / Accepted: 28 October 2020 © Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract People interact with other people in their daily life, either for work or for personal reasons. These interactions are often complex. Thus, interactions that an individual has with other individuals, to some extent, influence the decisions they make. There have been many efforts to uncover, explore, and measure the concept of social influence. Thus, modeling influence is an open and challenging problem where most evaluation models focus on online social networks. However, they fail to characterize some properties of social influence. To address the limitations of the previous approaches, we propose a novel Probabilistic Reasoning system for social INfluence analysis (PRIN) to examine the social influence process and elucidate the factors that affect it in an attempt to explain this phenomenon. In this paper, we present a model that quantitatively measures social influence in online social networks. Experiments on a real social network such as Twitter demonstrate that the proposed model significantly outperforms traditional feature engineering-based approaches. This suggests the effectiveness of this novel model when modeling and predicting social influence. Keywords Social influence analysis · Social networks · Bayesian network
1 Introduction Social influence (SI) is a common feature of everyday life: we either try to influence others or are influenced by them many times each day. For example, colleagues have a strong influence on one’s work, while friends have a strong influence on one’s daily life. This influence can be somewhat banal such as what type of shoes to buy—or more significant—such as whether to vote for one candidate versus others. Rashotte (2007) defined SI as a change in an individual’s thoughts, feelings, attitudes, and behaviors that results from interaction with another individual or a group. Influence is an invisible, complex, and subtle phenomenon that governs * Lea Vega [email protected] Andres Mendez‑Vazquez [email protected] Armando López‑Cuevas [email protected] 1
Research Center for Advanced Study from the National Polytechnic Institute, Zapopan, Mexico
Technological and Higher Education Institute of Monterrey, Monterrey, Mexico
2
social dynamics and user behaviors. Besides, SI takes many different forms and can be seen in processes of conformity, socialization, peer pressure, obedience, leadership, persuasion, minority influence, among others (Han and Li 2018). A social network (SN) is a social structure made up of individuals or organizations, which are connected by one or more specific types of interdependency, such as friendship, kinship, common interest, likes/dislikes, or relationships of beliefs, knowledge or prestige (Travers and Milgram 1967).
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