Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
4-2015
Abstract
Diffusion in social networks is an important research topic lately due to massive amount of information shared on social media and Web. As information diffuses, users express sentiments which can affect the sentiments of others. In this paper, we analyze how users reinforce or modify sentiment of one another based on a set of inter-dependent latent user factors as they are engaged in diffusion of event information. We introduce these sentiment-based latent user factors, namely influence, susceptibility and cynicalness. We also propose the ISC model to relate the three factors together and develop an iterative computation approach to derive them simultaneously. We evaluate the ISC model by conducting experiments on two separate sets of Twitter data collected from two real world events. The experiments show the top influential users tend to stay consistently influential while susceptibility and cynicalness of users could changed significantly across events.
Keywords
Twitter network, Sentiment diffusion
Discipline
Databases and Information Systems | Social Media
Research Areas
Data Science and Engineering
Publication
Advances in Information Retrieval: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29 - April 2, 2015. Proceedings
Volume
9022
First Page
411
Last Page
422
ISBN
9783319163536
Identifier
10.1007/978-3-319-16354-3_45
Publisher
Springer
City or Country
Cham
Citation
LEE, Roy Ka-Wei and LIM, Ee Peng.
Measuring user influence, susceptibility and cynicalness in sentiment diffusion. (2015). Advances in Information Retrieval: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29 - April 2, 2015. Proceedings. 9022, 411-422.
Available at: https://ink.library.smu.edu.sg/sis_research/2453
Copyright Owner and License
Authors/LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-319-16354-3_45