2 research outputs found
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