Identification of Opinion Leaders in Social Networks Based on Sentiment Analysis: Evidence from an Automotive Forum

DOI

10.2991/msota-16.2016.91How to use a DOI?

Keywords

social network; opinion leader; sentiment analysis; short text classification; automotive forum

Abstract

Opinion leadership of social network plays an important role in the fields of knowledge spreading, public sentiment controlling, marketing, etc. The opinions of users are derived from the reviews of topics, and the analysis of users' sentiment is helpful in recognizing users' emotional preference of opinion leaders. Thus, it is necessary to classify the forum posts and refine the posts with highly professional knowledge. We then improve the sentiment analysis due to the imbalanced datasets, and establish a comprehensive attention and emotion weight matrix. Accordingly, in this paper, we are going to propose a Leader-PageRank algorithm, which is based on the social network structure and emotional tendency. We do the comparative experiments on the automotive forum, and the results show that the Leader-PageRank algorithm can identify the positive opinion leaders in the professional fields effectively through connecting with the interactions in social networks.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Maoran Zhu
AU  - Xingkai Lin
AU  - Ting Lu
AU  - Hongwei Wang
PY  - 2016/12
DA  - 2016/12
TI  - Identification of Opinion Leaders in Social Networks Based on Sentiment Analysis: Evidence from an Automotive Forum
BT  - Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)
PB  - Atlantis Press
SP  - 412
EP  - 416
SN  - 2352-538X
UR  - https://doi.org/10.2991/msota-16.2016.91
DO  - 10.2991/msota-16.2016.91
ID  - Zhu2016/12
ER  -