請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92819完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 溫在弘 | zh_TW |
| dc.contributor.advisor | Tzai-Hung Wen | en |
| dc.contributor.author | 李蕙均 | zh_TW |
| dc.contributor.author | Hui-Chun Lee | en |
| dc.date.accessioned | 2024-07-02T16:07:59Z | - |
| dc.date.available | 2024-07-03 | - |
| dc.date.copyright | 2024-07-02 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-06-25 | - |
| dc.identifier.citation | Akther, T., & Nur, T. (2022). A model of factors influencing COVID-19 vaccine acceptance: A synthesis of the theory of reasoned action, conspiracy theory belief, awareness, perceived usefulness, and perceived ease of use. PLoS One, 17(1), e0261869. https://doi.org/10.1371/journal.pone.0261869
Badham, J., Kee, F., & Hunter, R. F. (2021). Network structure influence on simulated network interventions for behaviour change. Social Networks, 64, 55-62. Bauch, C. T. (2005). Imitation dynamics predict vaccinating behaviour. Proceedings of the Royal Society B: Biological Sciences, 272(1573), 1669-1675. Bauch, C. T., & Bhattacharyya, S. (2012). Evolutionary game theory and social learning can determine how vaccine scares unfold. PLoS Comput Biol, 8(4), e1002452. https://doi.org/10.1371/journal.pcbi.1002452 Bauch, C. T., & Earn, D. J. (2004). Vaccination and the theory of games. Proc Natl Acad Sci U S A, 101(36), 13391-13394. https://doi.org/10.1073/pnas.0403823101 Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the national academy of sciences, 99(suppl_3), 7280-7287. Chang, S. L., Piraveenan, M., Pattison, P., & Prokopenko, M. (2020). Game theoretic modelling of infectious disease dynamics and intervention methods: a review. J Biol Dyn, 14(1), 57-89. https://doi.org/10.1080/17513758.2020.1720322 Chen, F., Griffith, A., Cottrell, A., & Wong, Y. L. (2013). Behavioral responses to epidemics in an online experiment: using virtual diseases to study human behavior. PLoS One, 8(1), e52814. https://doi.org/10.1371/journal.pone.0052814 Cheng, H.-Y., Jian, S.-W., Liu, D.-P., Ng, T.-C., Huang, W.-T., & Lin, H.-H. (2020). Contact tracing assessment of COVID-19 transmission dynamics in Taiwan and risk at different exposure periods before and after symptom onset. JAMA internal medicine, 180(9), 1156-1163. Department of Health, Taipei City Government. (2024). 接種完COVID-19疫苗後，多久會有保護力？https://health.gov.taipei/News_Content.aspx?n=416BCB37CFFAC913&sms=87415A8B9CE81B16&s=525AA05E1DF0C19E Department of Health, Taipei City Government. (2024). 流感的傳染途徑、潛伏期與可傳染期為何？https://health.gov.taipei/News_Content.aspx?n=4EEA9B20817BE055&sms=65DC51EAB58A76FE&s=2CE94833BC96AE61 Ekman, I., Chanel, G., Järvelä, S., Kivikangas, J. M., Salminen, M., & Ravaja, N. (2011). Social Interaction in Games. Simulation & Gaming, 43(3), 321-338. https://doi.org/10.1177/1046878111422121 Elmerghany, A. H., & Paulus, G. (2017). Using minecraft as a geodesign tool for encouraging public participation in urban planning. GI_Forum2017, 5, 300-314. Epstein, J. M., Hatna, E., & Crodelle, J. (2021). Triple contagion: a two-fears epidemic model. Journal of the Royal Society Interface, 18(181), 20210186. Fine, P. E. (1993). Herd immunity: history, theory, practice. Epidemiologic reviews, 15(2), 265-302. Firth, J. A., Hellewell, J., Klepac, P., Kissler, S., Kucharski, A. J., & Spurgin, L. G. (2020). Using a real-world network to model localized COVID-19 control strategies. Nature medicine, 26(10), 1616-1622. Fu, F., Rosenbloom, D. I., Wang, L., & Nowak, M. A. (2011). Imitation dynamics of vaccination behaviour on social networks. Proc Biol Sci, 278(1702), 42-49. https://doi.org/10.1098/rspb.2010.1107 Greenstone, M., & Nigam, V. (2020). Does social distancing matter? University of Chicago, Becker Friedman Institute for Economics Working Paper(2020-26). Jiang, B., Yuan, L., Zou, R., Su, R., & Mi, Y. (2023). The effect of migration on vaccination dilemma in networked populations. Chaos, Solitons & Fractals, 170, 113411. John, T. J., & Samuel, R. (2000). Herd immunity and herd effect: new insights and definitions. European journal of epidemiology, 16, 601-606. Kabir, K. M. A., & Tanimoto, J. (2019). Evolutionary vaccination game approach in metapopulation migration model with information spreading on different graphs. Chaos, Solitons & Fractals, 120, 41-55. https://doi.org/10.1016/j.chaos.2019.01.013 Kerr, C. C., Stuart, R. M., Mistry, D., Abeysuriya, R. G., Rosenfeld, K., Hart, G. R., Nunez, R. C., Cohen, J. A., Selvaraj, P., Hagedorn, B., George, L., Jastrzebski, M., Izzo, A. S., Fowler, G., Palmer, A., Delport, D., Scott, N., Kelly, S. L., Bennette, C. S., . . . Klein, D. J. (2021). Covasim: An agent-based model of COVID-19 dynamics and interventions. PLoS Comput Biol, 17(7), e1009149. https://doi.org/10.1371/journal.pcbi.1009149 Kleczkowski, A., Maharaj, S., Rasmussen, S., Williams, L., & Cairns, N. (2015). Spontaneous social distancing in response to a simulated epidemic: a virtual experiment. BMC Public Health, 15, 973. https://doi.org/10.1186/s12889-015-2336-7 Lofgren, E. T., & Fefferman, N. H. (2007). The untapped potential of virtual game worlds to shed light on real world epidemics. The Lancet Infectious Diseases, 7(9), 625-629. https://doi.org/10.1016/s1473-3099(07)70212-8 Massey, D., Ahlqvist, O., Vatev, K., & Rush, J. (2019). A Massively Multi-user Online Game Framework for Agent-Based Spatial Simulation. In CyberGIS for Geospatial Discovery and Innovation (pp. 213-224). Springer. Montopoli, L., & Bauch, C. T. (2010). The free rider problem in vaccination policy and implications for global eradication of infectious diseases: a two-country game dynamic model. Nebel, S., Schneider, S., & Rey, G. D. (2016). Mining learning and crafting scientific experiments: a literature review on the use of minecraft in education and research. Journal of Educational Technology & Society, 19(2), 355-366. O''Sullivan, D., & Perry, G. L. (2013). Spatial simulation: exploring pattern and process. John Wiley & Sons. Opmeer, M., Dias, E., De Vogel, B., Tangerman, L., & Scholten, H. (2018). Minecraft in support of teaching sustainable spatial planning in secondary education. 10th International Conference on Computer Supported Education, Pan, Y., Ng, C. T., & Cheng, T. C. E. (2021). Effect of free-riding behavior on vaccination coverage with customer regret. Computers & Industrial Engineering, 159. https://doi.org/10.1016/j.cie.2021.107494 Perisic, A., & Bauch, C. T. (2009). Social contact networks and disease eradicability under voluntary vaccination. PLoS computational biology, 5(2), e1000280. Poletti, P., Caprile, B., Ajelli, M., Pugliese, A., & Merler, S. (2009). Spontaneous behavioural changes in response to epidemics. Journal of theoretical biology, 260(1), 31-40. R Izquierdo, L., S Izquierdo, S., & H Sandholm, W. (2019). Agent-Based Evolutionary Game Dynamics. Independent. Reluga, T. C. (2010). Game theory of social distancing in response to an epidemic. PLoS computational biology, 6(5), e1000793. Stahl, J.-P., Cohen, R., Denis, F., Gaudelus, J., Martinot, A., Lery, T., & Lepetit, H. (2016). The impact of the web and social networks on vaccination. New challenges and opportunities offered to fight against vaccine hesitancy. Medecine et maladies infectieuses, 46(3), 117-122. Taiwan Centers for Disease Control. (2024). 季節性流感防治。https://www.cdc.gov.tw/Category/QAPage/DQWXG19u2cXMH1jwGKXHug Taiwan Food and Drug Administration. (2021). COVID-19 疫苗不良事件通報摘要。https://www.fda.gov.tw/ World Health Organization. (2024). Middle East Respiratory Syndrome Coronavirus - Kingdom of Saudi Arabia. https://www.who.int/emergencies/disease-outbreak-news/item/2024-DON506. Worsley, M., & Bar-El, D. (2020). Spatial Reasoning in Minecraft: An Exploratory Study of In-Game Spatial Practices. Computersupported collaborative learning, 2. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92819 | - |
| dc.description.abstract | 疫苗在減緩疫情傳播方面起著至關重要的作用，但疫苗固有的風險和成本常使得提高疫苗覆蓋率變得具有挑戰性。社交網絡作為影響個人疫苗行為很重要的因素，因其與個人接觸和傳播風險以及疫苗資訊認知密切相關。接觸對象的免疫狀況也影響個人接種疫苗的動機，這可能促成了所謂的「搭便車效應」。本研究旨在使用《Minecraft》創建一個虛擬社會環境，以模擬這個虛擬社會中的疫情傳播。研究將蒐集玩家的真實遊戲數據，以捕捉疫情期間的人類行為。研究還將使用迴歸分析來檢驗現實生活行為與遊戲內行為之間的關聯性，以及疫苗報酬、社交網絡和個人疫苗行為之間的關係。 | zh_TW |
| dc.description.abstract | Vaccines serve as a crucial tool in mitigating the spread of epidemics, but the inherent risks and costs associated with vaccines often make it challenging to increase vaccine coverage. Social networks play a significant role in influencing individual vaccine behavior, as they are closely linked to personal contact and transmission risk, as well as vaccine information awareness. The immunity status of contacts also affects the individual''s motivation to get vaccinated, potentially contributing to the phenomenon known as the “free rider effect.” This study aims to create a virtual social environment using Minecraft to simulate the spread of an epidemic within this virtual society. It will collect real gameplay data from players to capture human behavior during an epidemic. The study will also employ regression analysis to examine the relationship between real-life behaviors and in-game behaviors, as well as the relationship between vaccination payoff, social networks, and individual vaccination behavior. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-07-02T16:07:59Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-07-02T16:07:59Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 謝辭 I
摘要 II Abstract III Contents IV List of Figures VI List of Tables VI Chapter 1 Introduction 1 1.1 Background 1 1.2 Objectives 3 Chapter 2 Literature Review 5 2.1 Vaccination and Networks 5 2.1.1 Exposure to Infection Risk 6 2.1.2 Perceived Vaccine Risk 7 2.1.3 Vaccination Game Theory and the Free-Rider Effect 8 2.2 Simulation Model 9 2.2.1 Agent-Based Model 10 2.2.2 Experimental Simulation 11 2.2.3 Minecraft as a Simulation Platform 12 Chapter 3 Methods 14 3.1 Simulation Environment 15 3.1.1 Minecraft 15 3.1.2 Time Settings 15 3.1.3 Activity Region 16 3.2 Players 16 3.2.1 Recruitment 16 3.2.2 Rules 18 3.2.3 Rewards 19 3.3 Villagers 19 3.3.1 Behavior 19 3.3.2 Trading System 20 3.3.3 Disease-related Settings 20 3.4 Epidemic Scenario 20 3.4.1 Contact and Infection 21 3.4.2 Vaccination 22 3.4.3 Parameters 23 3.5 Strategy and Reaction 24 3.5.1 Payoff 24 3.5.2 Perception and Information 25 3.6 Data Processing 26 3.6.1 Gaming Data 26 3.6.2 Questionnaire Data 29 3.6.3 Variables 30 3.7 Hypotheses 33 3.8 Models 34 3.8.1 Model 1: Real-world Behavior and In-game Behavior 34 3.8.2 Model 2: Factors Influencing Vaccination Behavior 36 Chapter 4 Results 38 4.1 Virtual Disease Transmission Scenario 38 4.2 Descriptive Statistics 39 4.3 Model Results 46 Chapter 5 Discussion 51 5.1 Interpretation of Findings 51 5.2 Limitations and Future Works 53 Chapter 6 Conclusion 55 References 57 Appendix 64 | - |
| dc.language.iso | en | - |
| dc.subject | 社交網絡 | zh_TW |
| dc.subject | 玩家模擬模型 | zh_TW |
| dc.subject | 代理人模擬模型 | zh_TW |
| dc.subject | 暴露風險 | zh_TW |
| dc.subject | 疫苗行為 | zh_TW |
| dc.subject | Vaccination Behavior | en |
| dc.subject | Exposure Risk | en |
| dc.subject | Agent-Based Model | en |
| dc.subject | Social Network | en |
| dc.subject | Player-Based Model | en |
| dc.title | 在多人線上遊戲中建立玩家模擬模型——討論接觸網絡對疫苗決策的影響 | zh_TW |
| dc.title | Building Player-Based Model in Multiplayer Online Games––the Impact of Exposure Networks on Vaccine Decisions | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 余清祥;陳怡如 | zh_TW |
| dc.contributor.oralexamcommittee | Ching-Syang Yue;Yi-Ju Chen | en |
| dc.subject.keyword | 玩家模擬模型,社交網絡,疫苗行為,暴露風險,代理人模擬模型, | zh_TW |
| dc.subject.keyword | Player-Based Model,Social Network,Vaccination Behavior,Exposure Risk,Agent-Based Model, | en |
| dc.relation.page | 67 | - |
| dc.identifier.doi | 10.6342/NTU202401310 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-06-25 | - |
| dc.contributor.author-college | 理學院 | - |
| dc.contributor.author-dept | 地理環境資源學系 | - |
| 顯示於系所單位： | 地理環境資源學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-112-2.pdf | 2.31 MB | Adobe PDF | 檢視/開啟 |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。