Modeling and Simulating of Network Public Opinion Evolution Based on Dynamic Reference Point of Prospect Theory
- DOI
- 10.2991/icmia-17.2017.81How to use a DOI?
- Keywords
- Dynamic Reference Point. Prospect Theory. Network Public Opinion. Evolution.
- Abstract
In order to better regulate the cyberspace and guide network public opinion in a right direction, forecasting the trend of network public opinion evolution has been a hotspot in recent years. Generally, netizens are often vulnerable to external factors, but more are affected by "bounded rationality" from the internal. Especially in emergencies, netizens often express their opinions on the basis of their own habits, intuition or experiences rather than searching enough information for decision-making. However, most existing quantitative analysis related to public opinion evolution focus on complete rationality of human, assuming that netizens are rational, intelligent, etc. to make perfect decisions, but it is inconsistent with the reality. Thus we introduced the dynamic reference point of Prospect Theory for constructing the modified HK model, aiming to analyze the migration of psychological reference point in the evolution of network public opinion. Compared with current common models, the proposed model, due to considering the dynamic psychological reference point under bounded rationality, is more realistic in the public opinion evolution.
- 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/).
Cite this article
TY - CONF AU - Jianhua Dai AU - Yanan Li PY - 2017/06 DA - 2017/06 TI - Modeling and Simulating of Network Public Opinion Evolution Based on Dynamic Reference Point of Prospect Theory BT - Proceedings of the 2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017) PB - Atlantis Press SP - 444 EP - 451 SN - 1951-6851 UR - https://doi.org/10.2991/icmia-17.2017.81 DO - 10.2991/icmia-17.2017.81 ID - Dai2017/06 ER -