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題名 自我或與他人競爭?使用競爭遊戲化設計之於社群群眾外包推薦系統
Competing with oneself or with others? Using competitive gamification design in community-based supported recommender system
作者 丁乃達
Ding, Nai-Da
貢獻者 林怡伶
Lin, Yi-Lin
丁乃達
Ding, Nai-Da
關鍵詞 推薦系統
群眾外包
遊戲化
當地社區
上下文
recommender system
context
crowdsourcing
gamification
local community
日期 2021
上傳時間 2-Sep-2021 15:57:32 (UTC+8)
摘要 從推薦物品中收集的即時上下文在上下文感知推薦系統中起著重要作用。例如，推薦系統可以通過及時上下文過濾掉尚未營業的餐廳。在這項研究中，我們提出了一種餐廳上下文感知推薦系統，該系統利用當地社區的群眾外包來收集即時上下文。我們設計了多個任務來滿足即時上下文收集的需求。此外，這項研究還討論了群眾外包中的關鍵挑戰，即如何激勵用戶參與。我們通過對擬議系統進行為期兩週的實地研究，比較了自我、社會競爭性遊戲化和混合這兩種遊戲化元素的遊戲化。參與者的反饋粗略地展示了使用當地社區的群眾外包來收集即時信息的可行性。實驗結果表明，混合競技遊戲化設計可以鼓勵高績效用戶和低產出用戶參與更多，而帶有自我競爭元素的遊戲化設計似乎可以激勵用戶完成更廣泛的任務。
Real-time contexts collected from items play important roles in the context-aware recommender system. For example, the recommender system can filter out the restaurants that are not open through the real-time contexts. In this study, we proposed a restaurants context-aware recommender system which harnesses local community crowdsourcing to collect real-time contexts. We design multiple tasks to fulfill the needs of real-time contexts collection. Furthermore, the key challenge in crowdsourcing applications, namely how to motivate users to participate, has also been discussed. We compared self-, social competitive gamification and the gamification that mixed these two gamification elements by conducting a two-week field study of the proposed system. The feedback from participants provides a rough demonstration of the feasibility of using local community crowdsourcing to collect real-time information. The results of experiment reveal that mixed competitive gamification design can encourage high preforming users and the user with lower output to engage more, and the gamified design with the self-competitive elements seems to motivate users do a wider variety of tasks.
參考文獻 Adomavicius, G., Mobasher, B., Ricci, F., andTuzhilin, A. 2011. “What a Recommender System Knows about Contextual Factors,” Springer, pp. 67–80.
Adomavicius, G., andTuzhilin, A. 2005. “Toward the next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions,” IEEE Transactions on Knowledge and Data Engineering (17:6), pp. 734–749.
Adomavicius, G., andTuzhilin, A. 2011. “Context-Aware Recommender Systems,” Recommender Systems Handbook.
Afuah, A., andTucci, C. 2012. “Crowdsourcing as a Solution to Distant Search,” Academy of Management Review (37:3), pp. 355–375.
Agapie, E., Teevan, J., andMonroy-hernández, A. 2015. “Crowdsourcing in the Field : A Case Study Using Local Crowds for Event Reporting,” Hcomp (2), pp. 2–11.
Alhamid, M. F., Rawashdeh, M., AlOsman, H., andElSaddik, A. 2013. “Leveraging Biosignal and Collaborative Filtering for Context-Aware Recommendation,” MIIRH 2013 - Proceedings of the 1st ACM International Workshop on Multimedia Indexing and Information Retrieval for Heathcare, Co-Located with ACM Multimedia 2013, pp. 41–48.
Banks, S., Rafter, R., andSmyth, B. 2015. “The Recommendation Game: Using a Game-with-a-Purpose to Generate Recommendation Data,” RecSys 2015 - Proceedings of the 9th ACM Conference on Recommender Systems, pp. 305–308.
Berri, J., Benlamri, R., andAtif, Y. 2006. “Ontology-Based Framework for Context-Aware Mobile Learning,” IWCMC 2006 - Proceedings of the 2006 International Wireless Communications and Mobile Computing Conference (2006), pp. 1307–1310.
Bowser, A., Hansen, D., He, Y., Boston, C., Reid, M., Gunnell, L., andPreece, J. 2013. “Using Gamification to Inspire New Citizen Science Volunteers,” ACM International Conference Proceeding Series, pp. 18–25.
Braunhofer, M., Ricci, F., Lamche, B., andWörndl, W. 2015. “A Context-Aware Model for Proactive Recommender Systems in the Tourism Domain,” MobileHCI 2015 - Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, pp. 1070–1075.
Chandler, D., andKapelner, A. 2013. “Breaking Monotony with Meaning: Motivation in Crowdsourcing Markets,” Journal of Economic Behavior and Organization (90), Elsevier B.V., pp. 123–133.
Chittilappilly, A. I., Chen, L., andAmer-Yahia, S. 2016. “A Survey of General-Purpose Crowdsourcing Techniques,” IEEE Transactions on Knowledge and Data Engineering (28:9), pp. 2246–2266.
Collection, a S., Innovation, O. F., From, I., andSloan, M. I. T. 2011. “Innovation From the Inside Out,” MIT Sloan Management Review (Winter 201:Winter 2011), pp. 35–41.
D’Ascenzo, F., Magni, M., Lazazzara, A., andZa, S. 2016. A Definition of Community Crowdsourcing Engagement and Application, (June).
Daniel, F., Kucherbaev, P., Cappiello, C., Benatallah, B., andAllahbakhsh, M. 2018. “Quality Control in Crowdsourcing: A Survey of Quality Attributes, Assessment Techniques and Assurance Actions,” ArXiv (51:1).
Davis, F. D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly: Management Information Systems (13:3), pp. 319–339.
Deng, D., Shahabi, C., andDemiryurek, U. 2013. “Maximizing the Number of Worker’s Self-Selected Tasks in Spatial Crowdsourcing,” GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, pp. 314–323.
Deterding, S. 2015. “The Lens of Intrinsic Skill Atoms: A Method for Gameful Design,” Human-Computer Interaction (30:3–4), pp. 294–335.
Deterding, S., Dixon, D., Khaled, R., andNacke, L. 2011. “From Game Design Elements to Gamefulness: Defining ‘Gamification,’” Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, MindTrek 2011, pp. 9–15.
Dey, A. K., Abowd, G. D., andSalber, D. 2001. “A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications,” Human-Computer Interaction (16:2–4), pp. 97–166.
Elnahrawy, E., andNath, B. 2004. Context-Aware Sensors, pp. 77–93.
Eroglu, S. A., andMachleit, K. A. 1990. “An Empirical Study of Retail Crowding: Antecedents and Consequences,” Journal of Retailing (66:2), pp. 201–221.
Feil, S., Kretzer, M., Werder, K., andMaedche, A. 2016. “Using Gamification to Tackle the Cold-Start Problem in Recommender Systems,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW (26-Februar), pp. 253–256.
Feng, Y., Jonathan Ye, H., Yu, Y., Yang, C., andCui, T. 2018. “Gamification Artifacts and Crowdsourcing Participation: Examining the Mediating Role of Intrinsic Motivations,” Computers in Human Behavior (81), Elsevier Ltd, pp. 124–136.
Fornell, C., andLarcker, D. F. 1981. “Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics,” Journal of Marketing Research (18:1), p. 39.
Funk, C., Tseng, M., Rajakumar, R., andHa, L. 2019. “Community-Driven Crowdsourcing: Data Collection with Local Developers,” LREC 2018 - 11th International Conference on Language Resources and Evaluation, pp. 1606–1609.
Gavalas, D., Konstantopoulos, C., Mastakas, K., andPantziou, G. 2014. “Mobile Recommender Systems in Tourism,” Journal of Network and Computer Applications (39:1), Elsevier, pp. 319–333.
Geiger, D., Fielt, E., Rosemann, M., andSchader, M. 2012. “Crowdsourcing Information Systems - Definition, Typology, and Design,” International Conference on Information Systems, ICIS 2012 (4), pp. 3562–3572.
Geiger, D., andSchader, M. 2014. “Personalized Task Recommendation in Crowdsourcing Information Systems - Current State of the Art,” Decision Support Systems (65:C), Elsevier B.V., pp. 3–16.
Goncalves, J., Ferreira, D., Hosio, S., Liu, Y., Rogstadius, J., Kukka, H., andKostakos, V. 2013. Crowdsourcing on the Spot: Altruistic Use of Public Displays, Feasibility, Performance, and Behaviours, pp. 753–762.
Ha, J., Park, K., andPark, J. 2016. “Which Restaurant Should I Choose? Herd Behavior in the Restaurant Industry,” Journal of Foodservice Business Research (19:4), Routledge, pp. 396–412.
Hackman, R., andOldham, G. 1976. “Motivation through the Design of Work: Test of a Theory,” Organizational Behavior and Human Performance (16:21), pp. 250–279.
Haklay, M., andWeber, P. 2008. “OpenStreet Map: User-Generated Street Maps,” IEEE Pervasive Computing (7:4), pp. 12–18.
Hamari, J. 2013. “Transforming Homo Economicus into Homo Ludens: A Field Experiment on Gamification in a Utilitarian Peer-to-Peer Trading Service,” Electronic Commerce Research and Applications (12:4), Elsevier B.V., pp. 236–245.
Hamari, J., andKoivisto, J. 2015. “Why Do People Use Gamification Services?,” International Journal of Information Management (35:4), pp. 419–431.
Hamari, J., Koivisto, J., andSarsa, H. 2014. “Does Gamification Work? - A Literature Review of Empirical Studies on Gamification,” Proceedings of the Annual Hawaii International Conference on System Sciences, IEEE, pp. 3025–3034.
Hao, A., Lee, C. S., andTan, W. C. W. 2019. “Fun with AEDs: Examining the Effects of a Gamified Mobile Crowdsourcing Application,” ACM International Conference Proceeding Series, pp. 207–211.
Van DerHeijden, H. 2004. “User Acceptance of Hedonic Information Systems,” MIS Quarterly (28:4), pp. 695–704.
Heimerl, K., Gawalt, B., Chen, K., Parikh, T. S., andHartmann, B. 2012. “Communitysourcing: Engaging Local Crowds to Perform Expert Work via Physical Kiosks,” Conference on Human Factors in Computing Systems - Proceedings, pp. 1539–1548.
Herlocker, J. L., Konstan, J. A., andRiedl, J. 2000. “Explaining Collaborative Filtering Recommendations,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, pp. 241–250.
Herpich, M., Rist, T., Seiderer, A., andAndré, E. 2017. “Towards a Gamified Recommender System for the Elderly,” ACM International Conference Proceeding Series (Part F1286), pp. 211–215.
Howe, J. 2006. “The Rise of Crowdsourcing,” Wired Magazine (14:06), pp. 1–5.
Huang, J., andZhou, L. 2021. “Social Gamification Affordances in the Green IT Services: Perspectives from Recognition and Social Overload,” Internet Research (31:2), pp. 737–761.
Huang, Z., Shijia, E., Zhang, J., Zhang, B., andJi, Z. 2016. “Pairwise Learning to Recommend with Both Users’ and Items’ Contextual Information,” IET Communications (10:16), pp. 2084–2090.
Jugovac, M., Jannach, D., andDortmund, T. U. 2017. Interacting with Recommenders — Overview and Research, (7:3).
Juho, H., Mimmi, S., andAntti, U. 2016. “The Sharing Economy: Why People Participate in Collaborative Consumption,” Journal of the American Society for Information Science and Technology (64:July), pp. 2047–2059.
Jung, J. H., Schneider, C., andValacich, J. 2010. “Enhancing the Motivational Affordance of Information Systems: The Effects of Real-Time Performance Feedback and Goal Setting in Group Collaboration Environments,” Management Science (56:4), pp. 724–742.
Kaufmann, N., Schulze, T., andVeit, D. 2011. “More than Fun and Money. Worker Motivation in Crowdsourcing – A Study on Mechanical Turk,” Proceedings of the Seventeenth Americas Conference on Information Systems (4:2009), pp. 1–11.
Kittur, A., Chi, E. H., andSuh, B. 2008. “Crowdsourcing User Studies with Mechanical Turk,” Conference on Human Factors in Computing Systems - Proceedings, pp. 453–456.
Korovina, O., Casati, F., Baez, M., Berestneva, O., andNielek, R. 2018. “Investigating Crowdsourcing as a Method to Collect Emotion Labels for Images,” Conference on Human Factors in Computing Systems - Proceedings (2018-April), pp. 1–6.
Kuo, W. T., Wang, Y. C., Tsai, R. T. H., andHsu, J. Y. J. 2015. “Contextual Restaurant Recommendation Utilizing Implicit Feedback,” 2015 24th Wireless and Optical Communication Conference, WOCC 2015, pp. 170–174.
Kwon, K. H., Halavais, A., andHavener, S. 2015. “Tweeting Badges: User Motivations for Displaying Achievement in Publicly Networked Environments,” Cyberpsychology, Behavior, and Social Networking (18:2), pp. 93–100.
Laureyssens, T., Coenen, T., Claeys, L., Mechant, P., Criel, J., andVan DeMoere, A. 2014. “ZWERM: A Modular Component Network Approach for an Urban Participation Game,” Conference on Human Factors in Computing Systems - Proceedings, pp. 3259–3268.
Lee, C. S., Goh, D. H., Zhou, Q., Sin, S. J., andTheng, Y. L. 2020. “Integrating Motives and Usability to Examine Community Crowdsourcing,” Proceedings of the Association for Information Science and Technology (57:1), pp. 2–4.
Lee, J. J., Ceyhan, P., Jordan-Cooley, W., andSung, W. 2013. “GREENIFY: A Real-World Action Game for Climate Change Education,” Simulation and Gaming (44:2–3), pp. 349–365.
Lee, T. Y., Dugan, C., Geyer, W., Ratchford, T., Rasmussen, J., Shami, N. S., andLupushor, S. 2013. “Experiments on Motivational Feedback for Crowdsourced Workers,” QaqProceedings of the 7th International Conference on Weblogs and Social Media, ICWSM 2013 (A:qaq), p. 1q.
Liu, D., Li, X., andSanthanam, R. 2013. “Digital Games and Beyond: What Happens When Players Compete?,” Angewandte Chemie International Edition, 6(11), 951–952. (37:1), pp. 111–124.
Liu, Z., Shabani, S., Balet, N. G., Sokhn, M., andCretton, F. 2018. “How to Motivate Participation and Improve Quality of Crowdsourcing When Building Accessibility Maps,” CCNC 2018 - 2018 15th IEEE Annual Consumer Communications and Networking Conference (2018-Janua), pp. 1–6.
Locke, E. A., andLatham, G. P. 2002. “Building a Practically Useful Theory of Goal Setting and Task Motivation: A 35-Year Odyssey,” American Psychologist (57:9), pp. 705–717.
Lu, J., Wu, D., Mao, M., Wang, W., andZhang, G. 2015. “Recommender System Application Developments: A Survey,” Decision Support Systems (74), Elsevier B.V., pp. 12–32.
Mashhadi, A., Quattrone, G., andCapra, L. 2013. “Putting Ubiquitous Crowd-Sourcing into Context,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 611–621.
Massung, E., Coyle, D., Cater, K., Jay, M., andPreist, C. 2013. “Using Crowdsourcing to Support Pro-Environmental Community Activism,” Conference on Human Factors in Computing Systems - Proceedings, pp. 371–380.
Mathews, A., Farley, S., Hightow-Weidman, L., Muessig, K., Rennie, S., andTucker, J. D. 2018. “Crowdsourcing and Community Engagement: A Qualitative Analysis of the 2BeatHIV Contest,” Journal of Virus Eradication (4:1), Elsevier Masson SAS, pp. 30–36.
McMillan, D. W., andChavis, D. M. 1986. “Sense of Community: A Definition and Theory,” Journal of Community Psychology (14:1), pp. 6–23.
Mergel, I. A. 2012. “Distributed Democracy: SeeClickFix.Com for Crowdsourced Issue Reporting,” SSRN Electronic Journal, pp. 0–19.
Misra, A., Gooze, A., Watkins, K., Asad, M., andLeDantec, C. 2014. “Crowdsourcing and Its Application to Transportation Data Collection and Management,” Transportation Research Record (2414), pp. 1–8.
Morschheuser, B., Hamari, J., andKoivisto, J. 2016. “Gamification in Crowdsourcing: A Review,” Proceedings of the Annual Hawaii International Conference on System Sciences (2016-March:October 2017), pp. 4375–4384.
Morschheuser, B., Hamari, J., Koivisto, J., andMaedche, A. 2017. “Gamified Crowdsourcing: Conceptualization, Literature Review, and Future Agenda,” International Journal of Human Computer Studies (106), Elsevier Ltd, pp. 26–43.
Morschheuser, B., Hamari, J., andMaedche, A. 2019. “Cooperation or Competition – When Do People Contribute More? A Field Experiment on Gamification of Crowdsourcing,” International Journal of Human Computer Studies (127:August 2017), pp. 7–24.
Morschheuser, B., Maedche, A., andWalter, D. 2017. “Designing Cooperative Gamification: Conceptualization and Prototypical Implementation,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 2410–2421.
Murillo-Zamorano, L. R., Ángel López Sánchez, J., andBueno Muñoz, C. 2020. “Gamified Crowdsourcing in Higher Education: A Theoretical Framework and a Case Study,” Thinking Skills and Creativity (36:November 2019), Elsevier, p. 100645.
Mysirlaki, S., andParaskeva, F. 2010. “Intrinsic Motivation and the Sense of Community in Multiplayer Games: An Extended Framework for Educational Game Design,” Proceedings - 14th Panhellenic Conference on Informatics, PCI 2010, pp. 223–227.
Neeraj, S., Oswald, C., andSivaselvan, B. 2018. “A Novel Gamification Approach to Recomendation Based Mobile Applications,” 2017 9th International Conference on Advanced Computing, ICoAC 2017, IEEE, pp. 157–164.
Oyibo, K., Orji, R., andVassileva, J. 2017. “Investigation of the Social Predictors of Competitive Behavior and the Moderating Effect of Culture,” UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization, pp. 419–424.
Panchendrarajan, R., Ahamed, N., Murugaiah, B., Sivakumar, P., Ranathunga, S., andPemasiri, A. 2016. Implicit Aspect Detection in Restaurant Reviews Using Cooccurence of Words, pp. 128–136.
Panniello, U., Tuzhilin, A., Gorgoglione, M., Palmisano, C., andPedone, A. 2009. “Experimental Comparison of Pre- vs. Post-Filtering Approaches in Context-Aware Recommender Systems,” RecSys’09 - Proceedings of the 3rd ACM Conference on Recommender Systems, pp. 265–268.
Park, Y., Oh, J., andYu, H. 2017. “RecTime: Real-Time Recommender System for Online Broadcasting,” Information Sciences (409–410), Elsevier Inc., pp. 1–16.
Pe-Than, E. P. P., Goh, D. H. L., andLee, C. S. 2014. “Making Work Fun: Investigating Antecedents of Perceived Enjoyment in Human Computation Games for Information Sharing,” Computers in Human Behavior (39), Elsevier Ltd, pp. 88–99.
Pian, Y., Lu, Y., Huang, Y., andBittencourt, I. I. 2020. “A Gamified Solution to the Cold-Start Problem of Intelligent Tutoring System,” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (12164 LNAI), pp. 376–381.
Plass, J. L., O’Keefe, P. A., Homer, B. D., Case, J., Hayward, E. O., Stein, M., andPerlin, K. 2013. “The Impact of Individual, Competitive, and Collaborative Mathematics Game Play on Learning, Performance, and Motivation,” Journal of Educational Psychology (105:4), pp. 1050–1066.
Preist, C., Massung, E., andCoyle, D. 2014. “Competing or Aiming to Be Average? Normification as a Means of Engaging Digital Volunteers,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 1222–1233.
Prezza, M., Pacilli, M. G., Barbaranelli, C., andZampatti, E. 2009. “The MTSOCS: A Multidimensional Sense of Community Scale for Local Communities,” Journal of Community Psychology (37:3), pp. 305–326.
Pu, P., Chen, L., andHu, R. 2012. “Evaluating Recommender Systems from the User’s Perspective: Survey of the State of the Art,” User Modeling and User-Adapted Interaction (22:4–5), pp. 317–355.
Rainie, L., Purcell, K., Mitchell, A., andRosenstiel, T. 2011. “Where People Get Information about Restaurants and Other Local Businesses,” Pew Research Center’s Internet and American Life Project., pp. 12–14.
Ramchurn, S. D., Huynh, T. D., Venanzi, M., andShi, B. 2013. Collabmap: Crowdsourcing Maps for Emergency Planning, pp. 326–335.
Ruiz-Correa, S., Santani, D., Ramírez-Salazar, B., Ruiz-Correa, I., Rendón-Huerta, F. A., Olmos-Carrillo, C., Sandoval-Mexicano, B. C., Arcos-Garcia, Á. H., Hasimoto-Beltrán, R., andGatica-Perez, D. 2017. “SenseCityVity: Mobile Crowdsourcing, Urban Awareness, and Collective Action in Mexico,” IEEE Pervasive Computing (16:2), pp. 44–53.
Saleh Al-Omoush, K., Orero-Blat, M., andRibeiro-Soriano, D. 2020. “The Role of Sense of Community in Harnessing the Wisdom of Crowds and Creating Collaborative Knowledge during the COVID-19 Pandemic,” Journal of Business Research, Elsevier Inc.
Salomoni, P., Prandi, C., Roccetti, M., Nisi, V., andJardim Nunes, N. 2015. “Crowdsourcing Urban Accessibility: Some Preliminary Experiences with Results,” ACM International Conference Proceeding Series (28), pp. 130–133.
Sasao, T., Konomi, S., Kostakos, V., Kuribayashi, K., andGoncalves, J. 2017. “Community Reminder: Participatory Contextual Reminder Environments for Local Communities,” International Journal of Human Computer Studies (102), Elsevier, pp. 41–53.
Schilit, B., Adams, N., andWant, R. 1995. “Context-Aware Computing Applications,” Mobile Computing Systems and Applications - Workshop Proceedings, pp. 85–90.
Shi, F., Ghedira, C., andMarini, J. L. 2015. “Context Adaptation for Smart Recommender Systems,” IT Professional (17:6), pp. 18–26.
Steinfeld, A., Zimmerman, J., Tomasic, A., Yoo, D., andAziz, R. 2011a. “Mobile Transit Information from Universal Design and Crowdsourcing,” Transportation Research Record (6346:2217), pp. 95–102.
Steinfeld, A., Zimmerman, J., Tomasic, A., Yoo, D., andAziz, R. 2011b. “Mobile Transit Information from Universal Design and Crowdsourcing,” Transportation Research Record (2217), pp. 95–102.
Sung S. Kim, andSon, J.-Y. 2009. “Out of Dedication or Constraint? A Dual Model of Post-Adoption Phenomena and Its Empirical Test in the Context of Online Services,” Angewandte Chemie International Edition, 6(11), 951–952. (33:1), pp. 49–70.
Sweetser, P., andWyeth, P. 2005. GameFlow: A Model for Evaluating Player Enjoyment in Games, (10507 LNCS:3), pp. 510–512.
Talò, C., Mannarini, T., andRochira, A. 2014. “Sense of Community and Community Participation: A Meta-Analytic Review,” Social Indicators Research (117:1), pp. 1–28.
Teodoro, R., Ozturk, P., Naaman, M., Mason, W., andLindqvist, J. 2014. “The Motivations and Experiences of the On-Demand Mobile Workforce,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 236–247.
Tintarev, N., andMasthoff, J. 2011. “Designing and Evaluating Explanations for Recommender Systems,” Recommender Systems Handbook.
Tiwari, S., andKaushik, S. 2014. “Information Enrichment for Tourist Spot Recommender System Using Location Aware Crowdsourcing,” Proceedings - IEEE International Conference on Mobile Data Management (2), pp. 11–14.
To, W. M., andChung, A. W. L. 2019. “An Innovative Approach in Data Collection for Restaurant Soundscape Study,” 177th Meeting of the Acoustical Society of America (36), p. 015001.
Vaish, R., Wyngarden, K., Chen, J., Cheung, B., andBernstein, M. S. 2014. “Twitch Crowdsourcing: Crowd Contributions in Short Bursts of Time,” Conference on Human Factors in Computing Systems - Proceedings, pp. 3645–3654.
Verbert, K., Ochoa, X., Bosnic, I., andDuval, E. 2007. “Recommender Systems for Learning : A Data-Oriented Survey and Future Challenges,” IEEE Transaction on Learning Technologies (6:1), pp. 1–20.
Wang, D., Yao, J., andMartin, B. A. S. 2021. “The Effects of Crowdedness and Safety Measures on Restaurant Patronage Choices and Perceptions in the COVID-19 Pandemic,” International Journal of Hospitality Management (95:October 2020), Elsevier Ltd, p. 102910.
Wang, X., Rosenblum, D., andWang, Y. 2012. “Context-Aware Mobile Music Recommendation for Daily Activities,” MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia, pp. 99–108.
Watkins, K. E., Ferris, B., Borning, A., Rutherford, G. S., andLayton, D. 2011. “Where Is My Bus? Impact of Mobile Real-Time Information on the Perceived and Actual Wait Time of Transit Riders,” Transportation Research Part A: Policy and Practice (45:8), Elsevier Ltd, pp. 839–848.
Wiggins, A., andCrowston, K. 2011. “From Conservation to Crowdsourcing: A Typology of Citizen Science,” Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 1–10.
Xi, N., andHamari, J. 2019. “Does Gamification Satisfy Needs? A Study on the Relationship between Gamification Features and Intrinsic Need Satisfaction,” International Journal of Information Management (46:November 2018), Elsevier, pp. 210–221.
Yamamoto, N., Saito, M., Miyazaki, M., andKoike, H. 2005. “Recommendation Algorithm Focused on Individual Viewpoints,” 2005 2nd IEEE Consumer Communications and Networking Conference, CCNC2005 (2005), pp. 65–70.
Zeng, J., Li, F., Liu, H., Wen, J., andHirokawa, S. 2016. “A Restaurant Recommender System Based on User Preference and Location in Mobile Environment,” Proceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 (2015), pp. 55–60.
Zhao, Y., andHan, Q. 2016. “Spatial Crowdsourcing: Current State and Future Directions,” IEEE Communications Magazine (54:7), pp. 102–107.
Zhou, X., Tang, J., Zhao, Y. (Chris), andWang, T. 2020. “Effects of Feedback Design and Dispositional Goal Orientations on Volunteer Performance in Citizen Science Projects,” Computers in Human Behavior (107:September 2019), Elsevier Ltd, p. 106266.
Zimmermann, A., Specht, M., andLorenz, A. 2005. “Personalization and Context Management,” User Modelling and User-Adapted Interaction (15:3–4), pp. 275–302.
描述 碩士
國立政治大學
資訊管理學系
108356027
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108356027
資料類型 thesis
dc.contributor.advisor 林怡伶zh_TW
dc.contributor.advisor Lin, Yi-Linen_US
dc.contributor.author (Authors) 丁乃達zh_TW
dc.contributor.author (Authors) Ding, Nai-Daen_US
dc.creator (作者) 丁乃達zh_TW
dc.creator (作者) Ding, Nai-Daen_US
dc.date (日期) 2021en_US
dc.date.accessioned 2-Sep-2021 15:57:32 (UTC+8)-
dc.date.available 2-Sep-2021 15:57:32 (UTC+8)-
dc.date.issued (上傳時間) 2-Sep-2021 15:57:32 (UTC+8)-
dc.identifier (Other Identifiers) G0108356027en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/136849-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 108356027zh_TW
dc.description.abstract (摘要) 從推薦物品中收集的即時上下文在上下文感知推薦系統中起著重要作用。例如，推薦系統可以通過及時上下文過濾掉尚未營業的餐廳。在這項研究中，我們提出了一種餐廳上下文感知推薦系統，該系統利用當地社區的群眾外包來收集即時上下文。我們設計了多個任務來滿足即時上下文收集的需求。此外，這項研究還討論了群眾外包中的關鍵挑戰，即如何激勵用戶參與。我們通過對擬議系統進行為期兩週的實地研究，比較了自我、社會競爭性遊戲化和混合這兩種遊戲化元素的遊戲化。參與者的反饋粗略地展示了使用當地社區的群眾外包來收集即時信息的可行性。實驗結果表明，混合競技遊戲化設計可以鼓勵高績效用戶和低產出用戶參與更多，而帶有自我競爭元素的遊戲化設計似乎可以激勵用戶完成更廣泛的任務。zh_TW
dc.description.abstract (摘要) Real-time contexts collected from items play important roles in the context-aware recommender system. For example, the recommender system can filter out the restaurants that are not open through the real-time contexts. In this study, we proposed a restaurants context-aware recommender system which harnesses local community crowdsourcing to collect real-time contexts. We design multiple tasks to fulfill the needs of real-time contexts collection. Furthermore, the key challenge in crowdsourcing applications, namely how to motivate users to participate, has also been discussed. We compared self-, social competitive gamification and the gamification that mixed these two gamification elements by conducting a two-week field study of the proposed system. The feedback from participants provides a rough demonstration of the feasibility of using local community crowdsourcing to collect real-time information. The results of experiment reveal that mixed competitive gamification design can encourage high preforming users and the user with lower output to engage more, and the gamified design with the self-competitive elements seems to motivate users do a wider variety of tasks.en_US
dc.description.tableofcontents Chapter 1 Introduction 1
Chapter 2 Related Works 7
2.1 Context in CARS 7
2.2 Local community-based crowdsourcing 8
2.3 Gamification in crowdsourcing 10
Chapter 3 Crowdsourcing-based recommendation framework 13
3.1 User Information Acquisition 13
3.2 Restaurant Information and Context Acquisition 15
3.2.1. Restaurant database 15
3.2.2. Types of collected contexts 16
3.2.3. Methods of contexts collection 17
3.2.4. Updating the map 21
3.3 Implementation of Interactive Recommender System 23
3.3.1. Recommender system and post-filtering approach 23
3.3.2. Context enrichment and interactive design 27
3.4 Incentive Mechanism 28
Chapter 4 Experimental Design 32
4.1 Experimental Procedures 32
4.2 Measurements 33
4.2.1. System logs 34
4.2.2. Questionnaire 34
Chapter 5 Analysis and Results 35
5.1 Behavioral Outcomes 37
5.2 Post Questionnaire 46
Chapter 6 Discussion 48
6.1 Comparison of gamification design 49
6.2 Community crowdsourcing CARS 52
Chapter 7 Conclusion 53
7.1 Contributions 54
7.2 Limitations and future research 55
Reference 57
Appendix 1 – Questionnaire 67		zh_TW
dc.format.extent 2306729 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108356027en_US
dc.subject (關鍵詞) 推薦系統zh_TW
dc.subject (關鍵詞) 群眾外包zh_TW
dc.subject (關鍵詞) 遊戲化zh_TW
dc.subject (關鍵詞) 當地社區zh_TW
dc.subject (關鍵詞) 上下文zh_TW
dc.subject (關鍵詞) recommender systemen_US
dc.subject (關鍵詞) contexten_US
dc.subject (關鍵詞) crowdsourcingen_US
dc.subject (關鍵詞) gamificationen_US
dc.subject (關鍵詞) local communityen_US
dc.title (題名) 自我或與他人競爭?使用競爭遊戲化設計之於社群群眾外包推薦系統zh_TW
dc.title (題名) Competing with oneself or with others? Using competitive gamification design in community-based supported recommender systemen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Adomavicius, G., Mobasher, B., Ricci, F., andTuzhilin, A. 2011. “What a Recommender System Knows about Contextual Factors,” Springer, pp. 67–80.
Adomavicius, G., andTuzhilin, A. 2005. “Toward the next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions,” IEEE Transactions on Knowledge and Data Engineering (17:6), pp. 734–749.
Adomavicius, G., andTuzhilin, A. 2011. “Context-Aware Recommender Systems,” Recommender Systems Handbook.
Afuah, A., andTucci, C. 2012. “Crowdsourcing as a Solution to Distant Search,” Academy of Management Review (37:3), pp. 355–375.
Agapie, E., Teevan, J., andMonroy-hernández, A. 2015. “Crowdsourcing in the Field : A Case Study Using Local Crowds for Event Reporting,” Hcomp (2), pp. 2–11.
Alhamid, M. F., Rawashdeh, M., AlOsman, H., andElSaddik, A. 2013. “Leveraging Biosignal and Collaborative Filtering for Context-Aware Recommendation,” MIIRH 2013 - Proceedings of the 1st ACM International Workshop on Multimedia Indexing and Information Retrieval for Heathcare, Co-Located with ACM Multimedia 2013, pp. 41–48.
Banks, S., Rafter, R., andSmyth, B. 2015. “The Recommendation Game: Using a Game-with-a-Purpose to Generate Recommendation Data,” RecSys 2015 - Proceedings of the 9th ACM Conference on Recommender Systems, pp. 305–308.
Berri, J., Benlamri, R., andAtif, Y. 2006. “Ontology-Based Framework for Context-Aware Mobile Learning,” IWCMC 2006 - Proceedings of the 2006 International Wireless Communications and Mobile Computing Conference (2006), pp. 1307–1310.
Bowser, A., Hansen, D., He, Y., Boston, C., Reid, M., Gunnell, L., andPreece, J. 2013. “Using Gamification to Inspire New Citizen Science Volunteers,” ACM International Conference Proceeding Series, pp. 18–25.
Braunhofer, M., Ricci, F., Lamche, B., andWörndl, W. 2015. “A Context-Aware Model for Proactive Recommender Systems in the Tourism Domain,” MobileHCI 2015 - Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, pp. 1070–1075.
Chandler, D., andKapelner, A. 2013. “Breaking Monotony with Meaning: Motivation in Crowdsourcing Markets,” Journal of Economic Behavior and Organization (90), Elsevier B.V., pp. 123–133.
Chittilappilly, A. I., Chen, L., andAmer-Yahia, S. 2016. “A Survey of General-Purpose Crowdsourcing Techniques,” IEEE Transactions on Knowledge and Data Engineering (28:9), pp. 2246–2266.
Collection, a S., Innovation, O. F., From, I., andSloan, M. I. T. 2011. “Innovation From the Inside Out,” MIT Sloan Management Review (Winter 201:Winter 2011), pp. 35–41.
D’Ascenzo, F., Magni, M., Lazazzara, A., andZa, S. 2016. A Definition of Community Crowdsourcing Engagement and Application, (June).
Daniel, F., Kucherbaev, P., Cappiello, C., Benatallah, B., andAllahbakhsh, M. 2018. “Quality Control in Crowdsourcing: A Survey of Quality Attributes, Assessment Techniques and Assurance Actions,” ArXiv (51:1).
Davis, F. D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly: Management Information Systems (13:3), pp. 319–339.
Deng, D., Shahabi, C., andDemiryurek, U. 2013. “Maximizing the Number of Worker’s Self-Selected Tasks in Spatial Crowdsourcing,” GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, pp. 314–323.
Deterding, S. 2015. “The Lens of Intrinsic Skill Atoms: A Method for Gameful Design,” Human-Computer Interaction (30:3–4), pp. 294–335.
Deterding, S., Dixon, D., Khaled, R., andNacke, L. 2011. “From Game Design Elements to Gamefulness: Defining ‘Gamification,’” Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, MindTrek 2011, pp. 9–15.
Dey, A. K., Abowd, G. D., andSalber, D. 2001. “A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications,” Human-Computer Interaction (16:2–4), pp. 97–166.
Elnahrawy, E., andNath, B. 2004. Context-Aware Sensors, pp. 77–93.
Eroglu, S. A., andMachleit, K. A. 1990. “An Empirical Study of Retail Crowding: Antecedents and Consequences,” Journal of Retailing (66:2), pp. 201–221.
Feil, S., Kretzer, M., Werder, K., andMaedche, A. 2016. “Using Gamification to Tackle the Cold-Start Problem in Recommender Systems,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW (26-Februar), pp. 253–256.
Feng, Y., Jonathan Ye, H., Yu, Y., Yang, C., andCui, T. 2018. “Gamification Artifacts and Crowdsourcing Participation: Examining the Mediating Role of Intrinsic Motivations,” Computers in Human Behavior (81), Elsevier Ltd, pp. 124–136.
Fornell, C., andLarcker, D. F. 1981. “Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics,” Journal of Marketing Research (18:1), p. 39.
Funk, C., Tseng, M., Rajakumar, R., andHa, L. 2019. “Community-Driven Crowdsourcing: Data Collection with Local Developers,” LREC 2018 - 11th International Conference on Language Resources and Evaluation, pp. 1606–1609.
Gavalas, D., Konstantopoulos, C., Mastakas, K., andPantziou, G. 2014. “Mobile Recommender Systems in Tourism,” Journal of Network and Computer Applications (39:1), Elsevier, pp. 319–333.
Geiger, D., Fielt, E., Rosemann, M., andSchader, M. 2012. “Crowdsourcing Information Systems - Definition, Typology, and Design,” International Conference on Information Systems, ICIS 2012 (4), pp. 3562–3572.
Geiger, D., andSchader, M. 2014. “Personalized Task Recommendation in Crowdsourcing Information Systems - Current State of the Art,” Decision Support Systems (65:C), Elsevier B.V., pp. 3–16.
Goncalves, J., Ferreira, D., Hosio, S., Liu, Y., Rogstadius, J., Kukka, H., andKostakos, V. 2013. Crowdsourcing on the Spot: Altruistic Use of Public Displays, Feasibility, Performance, and Behaviours, pp. 753–762.
Ha, J., Park, K., andPark, J. 2016. “Which Restaurant Should I Choose? Herd Behavior in the Restaurant Industry,” Journal of Foodservice Business Research (19:4), Routledge, pp. 396–412.
Hackman, R., andOldham, G. 1976. “Motivation through the Design of Work: Test of a Theory,” Organizational Behavior and Human Performance (16:21), pp. 250–279.
Haklay, M., andWeber, P. 2008. “OpenStreet Map: User-Generated Street Maps,” IEEE Pervasive Computing (7:4), pp. 12–18.
Hamari, J. 2013. “Transforming Homo Economicus into Homo Ludens: A Field Experiment on Gamification in a Utilitarian Peer-to-Peer Trading Service,” Electronic Commerce Research and Applications (12:4), Elsevier B.V., pp. 236–245.
Hamari, J., andKoivisto, J. 2015. “Why Do People Use Gamification Services?,” International Journal of Information Management (35:4), pp. 419–431.
Hamari, J., Koivisto, J., andSarsa, H. 2014. “Does Gamification Work? - A Literature Review of Empirical Studies on Gamification,” Proceedings of the Annual Hawaii International Conference on System Sciences, IEEE, pp. 3025–3034.
Hao, A., Lee, C. S., andTan, W. C. W. 2019. “Fun with AEDs: Examining the Effects of a Gamified Mobile Crowdsourcing Application,” ACM International Conference Proceeding Series, pp. 207–211.
Van DerHeijden, H. 2004. “User Acceptance of Hedonic Information Systems,” MIS Quarterly (28:4), pp. 695–704.
Heimerl, K., Gawalt, B., Chen, K., Parikh, T. S., andHartmann, B. 2012. “Communitysourcing: Engaging Local Crowds to Perform Expert Work via Physical Kiosks,” Conference on Human Factors in Computing Systems - Proceedings, pp. 1539–1548.
Herlocker, J. L., Konstan, J. A., andRiedl, J. 2000. “Explaining Collaborative Filtering Recommendations,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, pp. 241–250.
Herpich, M., Rist, T., Seiderer, A., andAndré, E. 2017. “Towards a Gamified Recommender System for the Elderly,” ACM International Conference Proceeding Series (Part F1286), pp. 211–215.
Howe, J. 2006. “The Rise of Crowdsourcing,” Wired Magazine (14:06), pp. 1–5.
Huang, J., andZhou, L. 2021. “Social Gamification Affordances in the Green IT Services: Perspectives from Recognition and Social Overload,” Internet Research (31:2), pp. 737–761.
Huang, Z., Shijia, E., Zhang, J., Zhang, B., andJi, Z. 2016. “Pairwise Learning to Recommend with Both Users’ and Items’ Contextual Information,” IET Communications (10:16), pp. 2084–2090.
Jugovac, M., Jannach, D., andDortmund, T. U. 2017. Interacting with Recommenders — Overview and Research, (7:3).
Juho, H., Mimmi, S., andAntti, U. 2016. “The Sharing Economy: Why People Participate in Collaborative Consumption,” Journal of the American Society for Information Science and Technology (64:July), pp. 2047–2059.
Jung, J. H., Schneider, C., andValacich, J. 2010. “Enhancing the Motivational Affordance of Information Systems: The Effects of Real-Time Performance Feedback and Goal Setting in Group Collaboration Environments,” Management Science (56:4), pp. 724–742.
Kaufmann, N., Schulze, T., andVeit, D. 2011. “More than Fun and Money. Worker Motivation in Crowdsourcing – A Study on Mechanical Turk,” Proceedings of the Seventeenth Americas Conference on Information Systems (4:2009), pp. 1–11.
Kittur, A., Chi, E. H., andSuh, B. 2008. “Crowdsourcing User Studies with Mechanical Turk,” Conference on Human Factors in Computing Systems - Proceedings, pp. 453–456.
Korovina, O., Casati, F., Baez, M., Berestneva, O., andNielek, R. 2018. “Investigating Crowdsourcing as a Method to Collect Emotion Labels for Images,” Conference on Human Factors in Computing Systems - Proceedings (2018-April), pp. 1–6.
Kuo, W. T., Wang, Y. C., Tsai, R. T. H., andHsu, J. Y. J. 2015. “Contextual Restaurant Recommendation Utilizing Implicit Feedback,” 2015 24th Wireless and Optical Communication Conference, WOCC 2015, pp. 170–174.
Kwon, K. H., Halavais, A., andHavener, S. 2015. “Tweeting Badges: User Motivations for Displaying Achievement in Publicly Networked Environments,” Cyberpsychology, Behavior, and Social Networking (18:2), pp. 93–100.
Laureyssens, T., Coenen, T., Claeys, L., Mechant, P., Criel, J., andVan DeMoere, A. 2014. “ZWERM: A Modular Component Network Approach for an Urban Participation Game,” Conference on Human Factors in Computing Systems - Proceedings, pp. 3259–3268.
Lee, C. S., Goh, D. H., Zhou, Q., Sin, S. J., andTheng, Y. L. 2020. “Integrating Motives and Usability to Examine Community Crowdsourcing,” Proceedings of the Association for Information Science and Technology (57:1), pp. 2–4.
Lee, J. J., Ceyhan, P., Jordan-Cooley, W., andSung, W. 2013. “GREENIFY: A Real-World Action Game for Climate Change Education,” Simulation and Gaming (44:2–3), pp. 349–365.
Lee, T. Y., Dugan, C., Geyer, W., Ratchford, T., Rasmussen, J., Shami, N. S., andLupushor, S. 2013. “Experiments on Motivational Feedback for Crowdsourced Workers,” QaqProceedings of the 7th International Conference on Weblogs and Social Media, ICWSM 2013 (A:qaq), p. 1q.
Liu, D., Li, X., andSanthanam, R. 2013. “Digital Games and Beyond: What Happens When Players Compete?,” Angewandte Chemie International Edition, 6(11), 951–952. (37:1), pp. 111–124.
Liu, Z., Shabani, S., Balet, N. G., Sokhn, M., andCretton, F. 2018. “How to Motivate Participation and Improve Quality of Crowdsourcing When Building Accessibility Maps,” CCNC 2018 - 2018 15th IEEE Annual Consumer Communications and Networking Conference (2018-Janua), pp. 1–6.
Locke, E. A., andLatham, G. P. 2002. “Building a Practically Useful Theory of Goal Setting and Task Motivation: A 35-Year Odyssey,” American Psychologist (57:9), pp. 705–717.
Lu, J., Wu, D., Mao, M., Wang, W., andZhang, G. 2015. “Recommender System Application Developments: A Survey,” Decision Support Systems (74), Elsevier B.V., pp. 12–32.
Mashhadi, A., Quattrone, G., andCapra, L. 2013. “Putting Ubiquitous Crowd-Sourcing into Context,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 611–621.
Massung, E., Coyle, D., Cater, K., Jay, M., andPreist, C. 2013. “Using Crowdsourcing to Support Pro-Environmental Community Activism,” Conference on Human Factors in Computing Systems - Proceedings, pp. 371–380.
Mathews, A., Farley, S., Hightow-Weidman, L., Muessig, K., Rennie, S., andTucker, J. D. 2018. “Crowdsourcing and Community Engagement: A Qualitative Analysis of the 2BeatHIV Contest,” Journal of Virus Eradication (4:1), Elsevier Masson SAS, pp. 30–36.
McMillan, D. W., andChavis, D. M. 1986. “Sense of Community: A Definition and Theory,” Journal of Community Psychology (14:1), pp. 6–23.
Mergel, I. A. 2012. “Distributed Democracy: SeeClickFix.Com for Crowdsourced Issue Reporting,” SSRN Electronic Journal, pp. 0–19.
Misra, A., Gooze, A., Watkins, K., Asad, M., andLeDantec, C. 2014. “Crowdsourcing and Its Application to Transportation Data Collection and Management,” Transportation Research Record (2414), pp. 1–8.
Morschheuser, B., Hamari, J., andKoivisto, J. 2016. “Gamification in Crowdsourcing: A Review,” Proceedings of the Annual Hawaii International Conference on System Sciences (2016-March:October 2017), pp. 4375–4384.
Morschheuser, B., Hamari, J., Koivisto, J., andMaedche, A. 2017. “Gamified Crowdsourcing: Conceptualization, Literature Review, and Future Agenda,” International Journal of Human Computer Studies (106), Elsevier Ltd, pp. 26–43.
Morschheuser, B., Hamari, J., andMaedche, A. 2019. “Cooperation or Competition – When Do People Contribute More? A Field Experiment on Gamification of Crowdsourcing,” International Journal of Human Computer Studies (127:August 2017), pp. 7–24.
Morschheuser, B., Maedche, A., andWalter, D. 2017. “Designing Cooperative Gamification: Conceptualization and Prototypical Implementation,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 2410–2421.
Murillo-Zamorano, L. R., Ángel López Sánchez, J., andBueno Muñoz, C. 2020. “Gamified Crowdsourcing in Higher Education: A Theoretical Framework and a Case Study,” Thinking Skills and Creativity (36:November 2019), Elsevier, p. 100645.
Mysirlaki, S., andParaskeva, F. 2010. “Intrinsic Motivation and the Sense of Community in Multiplayer Games: An Extended Framework for Educational Game Design,” Proceedings - 14th Panhellenic Conference on Informatics, PCI 2010, pp. 223–227.
Neeraj, S., Oswald, C., andSivaselvan, B. 2018. “A Novel Gamification Approach to Recomendation Based Mobile Applications,” 2017 9th International Conference on Advanced Computing, ICoAC 2017, IEEE, pp. 157–164.
Oyibo, K., Orji, R., andVassileva, J. 2017. “Investigation of the Social Predictors of Competitive Behavior and the Moderating Effect of Culture,” UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization, pp. 419–424.
Panchendrarajan, R., Ahamed, N., Murugaiah, B., Sivakumar, P., Ranathunga, S., andPemasiri, A. 2016. Implicit Aspect Detection in Restaurant Reviews Using Cooccurence of Words, pp. 128–136.
Panniello, U., Tuzhilin, A., Gorgoglione, M., Palmisano, C., andPedone, A. 2009. “Experimental Comparison of Pre- vs. Post-Filtering Approaches in Context-Aware Recommender Systems,” RecSys’09 - Proceedings of the 3rd ACM Conference on Recommender Systems, pp. 265–268.
Park, Y., Oh, J., andYu, H. 2017. “RecTime: Real-Time Recommender System for Online Broadcasting,” Information Sciences (409–410), Elsevier Inc., pp. 1–16.
Pe-Than, E. P. P., Goh, D. H. L., andLee, C. S. 2014. “Making Work Fun: Investigating Antecedents of Perceived Enjoyment in Human Computation Games for Information Sharing,” Computers in Human Behavior (39), Elsevier Ltd, pp. 88–99.
Pian, Y., Lu, Y., Huang, Y., andBittencourt, I. I. 2020. “A Gamified Solution to the Cold-Start Problem of Intelligent Tutoring System,” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (12164 LNAI), pp. 376–381.
Plass, J. L., O’Keefe, P. A., Homer, B. D., Case, J., Hayward, E. O., Stein, M., andPerlin, K. 2013. “The Impact of Individual, Competitive, and Collaborative Mathematics Game Play on Learning, Performance, and Motivation,” Journal of Educational Psychology (105:4), pp. 1050–1066.
Preist, C., Massung, E., andCoyle, D. 2014. “Competing or Aiming to Be Average? Normification as a Means of Engaging Digital Volunteers,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 1222–1233.
Prezza, M., Pacilli, M. G., Barbaranelli, C., andZampatti, E. 2009. “The MTSOCS: A Multidimensional Sense of Community Scale for Local Communities,” Journal of Community Psychology (37:3), pp. 305–326.
Pu, P., Chen, L., andHu, R. 2012. “Evaluating Recommender Systems from the User’s Perspective: Survey of the State of the Art,” User Modeling and User-Adapted Interaction (22:4–5), pp. 317–355.
Rainie, L., Purcell, K., Mitchell, A., andRosenstiel, T. 2011. “Where People Get Information about Restaurants and Other Local Businesses,” Pew Research Center’s Internet and American Life Project., pp. 12–14.
Ramchurn, S. D., Huynh, T. D., Venanzi, M., andShi, B. 2013. Collabmap: Crowdsourcing Maps for Emergency Planning, pp. 326–335.
Ruiz-Correa, S., Santani, D., Ramírez-Salazar, B., Ruiz-Correa, I., Rendón-Huerta, F. A., Olmos-Carrillo, C., Sandoval-Mexicano, B. C., Arcos-Garcia, Á. H., Hasimoto-Beltrán, R., andGatica-Perez, D. 2017. “SenseCityVity: Mobile Crowdsourcing, Urban Awareness, and Collective Action in Mexico,” IEEE Pervasive Computing (16:2), pp. 44–53.
Saleh Al-Omoush, K., Orero-Blat, M., andRibeiro-Soriano, D. 2020. “The Role of Sense of Community in Harnessing the Wisdom of Crowds and Creating Collaborative Knowledge during the COVID-19 Pandemic,” Journal of Business Research, Elsevier Inc.
Salomoni, P., Prandi, C., Roccetti, M., Nisi, V., andJardim Nunes, N. 2015. “Crowdsourcing Urban Accessibility: Some Preliminary Experiences with Results,” ACM International Conference Proceeding Series (28), pp. 130–133.
Sasao, T., Konomi, S., Kostakos, V., Kuribayashi, K., andGoncalves, J. 2017. “Community Reminder: Participatory Contextual Reminder Environments for Local Communities,” International Journal of Human Computer Studies (102), Elsevier, pp. 41–53.
Schilit, B., Adams, N., andWant, R. 1995. “Context-Aware Computing Applications,” Mobile Computing Systems and Applications - Workshop Proceedings, pp. 85–90.
Shi, F., Ghedira, C., andMarini, J. L. 2015. “Context Adaptation for Smart Recommender Systems,” IT Professional (17:6), pp. 18–26.
Steinfeld, A., Zimmerman, J., Tomasic, A., Yoo, D., andAziz, R. 2011a. “Mobile Transit Information from Universal Design and Crowdsourcing,” Transportation Research Record (6346:2217), pp. 95–102.
Steinfeld, A., Zimmerman, J., Tomasic, A., Yoo, D., andAziz, R. 2011b. “Mobile Transit Information from Universal Design and Crowdsourcing,” Transportation Research Record (2217), pp. 95–102.
Sung S. Kim, andSon, J.-Y. 2009. “Out of Dedication or Constraint? A Dual Model of Post-Adoption Phenomena and Its Empirical Test in the Context of Online Services,” Angewandte Chemie International Edition, 6(11), 951–952. (33:1), pp. 49–70.
Sweetser, P., andWyeth, P. 2005. GameFlow: A Model for Evaluating Player Enjoyment in Games, (10507 LNCS:3), pp. 510–512.
Talò, C., Mannarini, T., andRochira, A. 2014. “Sense of Community and Community Participation: A Meta-Analytic Review,” Social Indicators Research (117:1), pp. 1–28.
Teodoro, R., Ozturk, P., Naaman, M., Mason, W., andLindqvist, J. 2014. “The Motivations and Experiences of the On-Demand Mobile Workforce,” Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 236–247.
Tintarev, N., andMasthoff, J. 2011. “Designing and Evaluating Explanations for Recommender Systems,” Recommender Systems Handbook.
Tiwari, S., andKaushik, S. 2014. “Information Enrichment for Tourist Spot Recommender System Using Location Aware Crowdsourcing,” Proceedings - IEEE International Conference on Mobile Data Management (2), pp. 11–14.
To, W. M., andChung, A. W. L. 2019. “An Innovative Approach in Data Collection for Restaurant Soundscape Study,” 177th Meeting of the Acoustical Society of America (36), p. 015001.
Vaish, R., Wyngarden, K., Chen, J., Cheung, B., andBernstein, M. S. 2014. “Twitch Crowdsourcing: Crowd Contributions in Short Bursts of Time,” Conference on Human Factors in Computing Systems - Proceedings, pp. 3645–3654.
Verbert, K., Ochoa, X., Bosnic, I., andDuval, E. 2007. “Recommender Systems for Learning : A Data-Oriented Survey and Future Challenges,” IEEE Transaction on Learning Technologies (6:1), pp. 1–20.
Wang, D., Yao, J., andMartin, B. A. S. 2021. “The Effects of Crowdedness and Safety Measures on Restaurant Patronage Choices and Perceptions in the COVID-19 Pandemic,” International Journal of Hospitality Management (95:October 2020), Elsevier Ltd, p. 102910.
Wang, X., Rosenblum, D., andWang, Y. 2012. “Context-Aware Mobile Music Recommendation for Daily Activities,” MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia, pp. 99–108.
Watkins, K. E., Ferris, B., Borning, A., Rutherford, G. S., andLayton, D. 2011. “Where Is My Bus? Impact of Mobile Real-Time Information on the Perceived and Actual Wait Time of Transit Riders,” Transportation Research Part A: Policy and Practice (45:8), Elsevier Ltd, pp. 839–848.
Wiggins, A., andCrowston, K. 2011. “From Conservation to Crowdsourcing: A Typology of Citizen Science,” Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 1–10.
Xi, N., andHamari, J. 2019. “Does Gamification Satisfy Needs? A Study on the Relationship between Gamification Features and Intrinsic Need Satisfaction,” International Journal of Information Management (46:November 2018), Elsevier, pp. 210–221.
Yamamoto, N., Saito, M., Miyazaki, M., andKoike, H. 2005. “Recommendation Algorithm Focused on Individual Viewpoints,” 2005 2nd IEEE Consumer Communications and Networking Conference, CCNC2005 (2005), pp. 65–70.
Zeng, J., Li, F., Liu, H., Wen, J., andHirokawa, S. 2016. “A Restaurant Recommender System Based on User Preference and Location in Mobile Environment,” Proceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 (2015), pp. 55–60.
Zhao, Y., andHan, Q. 2016. “Spatial Crowdsourcing: Current State and Future Directions,” IEEE Communications Magazine (54:7), pp. 102–107.
Zhou, X., Tang, J., Zhao, Y. (Chris), andWang, T. 2020. “Effects of Feedback Design and Dispositional Goal Orientations on Volunteer Performance in Citizen Science Projects,” Computers in Human Behavior (107:September 2019), Elsevier Ltd, p. 106266.
Zimmermann, A., Specht, M., andLorenz, A. 2005. “Personalization and Context Management,” User Modelling and User-Adapted Interaction (15:3–4), pp. 275–302.		zh_TW
dc.identifier.doi (DOI) 10.6814/NCCU202101340en_US