Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities
Abstract
:1. Introduction
2. Literature Review
3. Evolutionary Game Theoretical Model
3.1. Problem Description and Model Assumptions
3.2. Model Calculation and Stability Analysis
4. Numerical Simulation Experiment
5. Conclusions, Policy Implications, and Future Research
5.1. Conclusions
5.2. Policy Implications
5.3. Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Notation | Description |
---|---|
M | Medical service support obtained by users after disclosing their personal information, |
E | Emotional support obtained by users after disclosing their personal information, |
I | Information support obtained by users after disclosing their personal information, |
Loss of users after their privacy leaks, | |
Loss of OHCs after users’ privacy leaks, | |
Rewards from the OHCs after users disclose their personal information, | |
Costs of implementing the “negative protection” strategy in the OHCs, | |
Extra costs of implementing the “positive protection” strategy in the OHCs, | |
B | Benefits of user disclosure of personal information for OHCs influence, |
a | Probability of users disclosing personal information to medical personnel, |
b | Probability of users disclosing personal information to other ordinary users, |
c | Probability of privacy leakage under the “positive protection” strategy, |
d | Probability of privacy leakage under the “negative protection” strategy, |
Online Health Communities | |||
---|---|---|---|
Positive Protection | Positive Protection | ||
Users | Disclosure | ||
Non-disclosure |
Equilibrium Points | ||
---|---|---|
D1 (0, 0) | ||
D2 (1, 0) | ||
D3 (0, 1) | ||
D4 (1, 1) | ||
D5 (x*, y*) | 0 |
Scenario | Conditions | Determinant | Equilibrium Point | ||||
---|---|---|---|---|---|---|---|
(0, 0) | (1, 0) | (0, 1) | (1, 1) | (x*, y*) | |||
1 | |||||||
0 | |||||||
Stability | ESS | Saddle point | Saddle point | Unstable point | Center point | ||
2 | |||||||
0 | |||||||
Stability | ESS | Saddle point | Saddle point | Unstable point | Center point | ||
3 | |||||||
0 | |||||||
Stability | ESS | Unstable point | Saddle point | Saddle point | Center point | ||
4 | |||||||
0 | |||||||
Stability | ESS | Saddle point | Unstable point | Saddle point | Center point | ||
5 | |||||||
0 | |||||||
Stability | ESS | Saddle point | Unstable point | Saddle point | Center point | ||
6 | |||||||
0 | |||||||
Stability | ESS | Unstable point | Unstable point | ESS | Center point | ||
7 | |||||||
0 | |||||||
Stability | Saddle point | ESS | Unstable point | Saddle point | Center point | ||
8 | |||||||
0 | |||||||
Stability | Saddle point | ESS | Unstable point | Saddle point | Center point | ||
9 | |||||||
0 | |||||||
Stability | Saddle point | Saddle point | Unstable point | ESS | Center point |
Scenario | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 5 | 2.5 | 1.5 | 1 | 0.6 | 0.4 | 5 | 5 | 20 | 20 | 10 | 15 | 0.3 | 0.7 |
2 | 5 | 2.5 | 1.5 | 1 | 0.6 | 0.4 | 5 | 5 | 20 | 20 | 10 | 10 | 0.3 | 0.7 |
3 | 5 | 2.5 | 1.5 | 1 | 0.6 | 0.4 | 5 | 5 | 20 | 20 | 10 | 5 | 0.3 | 0.7 |
4 | 10 | 5 | 3 | 2 | 0.6 | 0.4 | 10 | 5 | 20 | 20 | 10 | 15 | 0.3 | 0.7 |
5 | 10 | 5 | 3 | 2 | 0.6 | 0.4 | 10 | 5 | 20 | 20 | 10 | 10 | 0.3 | 0.7 |
6 | 10 | 5 | 3 | 2 | 0.6 | 0.4 | 10 | 5 | 20 | 20 | 10 | 5 | 0.3 | 0.7 |
7 | 20 | 10 | 6 | 4 | 0.6 | 0.4 | 20 | 5 | 20 | 20 | 10 | 15 | 0.3 | 0.7 |
8 | 20 | 10 | 6 | 4 | 0.6 | 0.4 | 20 | 5 | 20 | 20 | 10 | 10 | 0.3 | 0.7 |
9 | 20 | 10 | 6 | 4 | 0.6 | 0.4 | 20 | 5 | 20 | 20 | 10 | 5 | 0.3 | 0.7 |
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Xu, Z.; Chen, X.; Hong, Y. Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities. Appl. Sci. 2022, 12, 6603. https://doi.org/10.3390/app12136603
Xu Z, Chen X, Hong Y. Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities. Applied Sciences. 2022; 12(13):6603. https://doi.org/10.3390/app12136603
Chicago/Turabian StyleXu, Zhongyang, Xihui Chen, and Yuanxiao Hong. 2022. "Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities" Applied Sciences 12, no. 13: 6603. https://doi.org/10.3390/app12136603
APA StyleXu, Z., Chen, X., & Hong, Y. (2022). Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities. Applied Sciences, 12(13), 6603. https://doi.org/10.3390/app12136603