How to Find Opinion Leader on the Online Social Network?

Online social networks (OSNs) provide a platform for individuals to share information, exchange ideas and build social connections beyond in-person interactions. For a specific topic or community, opinion leaders are individuals who have a significant influence on others' opinions. Detecting and modeling opinion leaders is crucial as they play a vital role in shaping public opinion and driving online conversations. Existing research have extensively explored various methods for detecting opinion leaders, but there is a lack of consensus between definitions and methods. It is important to note that the term "important node" in graph theory does not necessarily align with the concept of "opinion leader" in social psychology. This paper aims to address this issue by introducing the methodologies for identifying influential nodes in OSNs and providing a corresponding definition of opinion leaders in relation to social psychology. The key novelty is to review connections and cross-compare different approaches that have origins in: graph theory, natural language processing, social psychology, control theory, and graph sampling. We discuss how they tell a different technical tale of influence and also propose how some of the approaches can be combined via networked dynamical systems modeling. A case study is performed on Twitter data to compare the performance of different methodologies discussed. The primary objective of this work is to elucidate the progression of opinion leader detection on OSNs and inspire further research in understanding the dynamics of opinion evolution within the field.