{"title":"随机还是优先?共同创造社区中用户行为的演化机制","authors":"Fanshun Zhang, Congdong Li, Cejun Cao, Zhiwei Zhang","doi":"10.1007/s10588-021-09357-6","DOIUrl":null,"url":null,"abstract":"<p>The objective of this paper is to examine the evolutionary mechanism regarding how a co-creation community network evolves as the growth of user interaction, which differs from the existing studies concentrating on the explanation of the forward problems of information management systems (e.g. motivational identification of user participation and examination of users’ outcomes). To achieve this objective, network generation model is formulated as nodes of users, ties of user’s interactions, random process, and preferential attachment. Then, real networks formulated by practice and artificial networks generated by the proposed model are compared by cumulative degree distribution, so as to validate the feasibility of the proposed model and to explain user behavior from the perspective of link formulation. Results indicate that: (i) new users account for main contributions for the development of co-creation community; (ii) new users prefer to interact high-influence all the time, while old users interchangeably choose preferential attachment or random linking in different time periods, (iii) the initial number of users, the probability for choosing preferential attachment or random attachment has a great influence on the properties of a user interactive network.</p>","PeriodicalId":50648,"journal":{"name":"Computational and Mathematical Organization Theory","volume":"157 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Random or preferential? Evolutionary mechanism of user behavior in co-creation community\",\"authors\":\"Fanshun Zhang, Congdong Li, Cejun Cao, Zhiwei Zhang\",\"doi\":\"10.1007/s10588-021-09357-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The objective of this paper is to examine the evolutionary mechanism regarding how a co-creation community network evolves as the growth of user interaction, which differs from the existing studies concentrating on the explanation of the forward problems of information management systems (e.g. motivational identification of user participation and examination of users’ outcomes). To achieve this objective, network generation model is formulated as nodes of users, ties of user’s interactions, random process, and preferential attachment. Then, real networks formulated by practice and artificial networks generated by the proposed model are compared by cumulative degree distribution, so as to validate the feasibility of the proposed model and to explain user behavior from the perspective of link formulation. Results indicate that: (i) new users account for main contributions for the development of co-creation community; (ii) new users prefer to interact high-influence all the time, while old users interchangeably choose preferential attachment or random linking in different time periods, (iii) the initial number of users, the probability for choosing preferential attachment or random attachment has a great influence on the properties of a user interactive network.</p>\",\"PeriodicalId\":50648,\"journal\":{\"name\":\"Computational and Mathematical Organization Theory\",\"volume\":\"157 1\",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2022-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational and Mathematical Organization Theory\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s10588-021-09357-6\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and Mathematical Organization Theory","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s10588-021-09357-6","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Random or preferential? Evolutionary mechanism of user behavior in co-creation community
The objective of this paper is to examine the evolutionary mechanism regarding how a co-creation community network evolves as the growth of user interaction, which differs from the existing studies concentrating on the explanation of the forward problems of information management systems (e.g. motivational identification of user participation and examination of users’ outcomes). To achieve this objective, network generation model is formulated as nodes of users, ties of user’s interactions, random process, and preferential attachment. Then, real networks formulated by practice and artificial networks generated by the proposed model are compared by cumulative degree distribution, so as to validate the feasibility of the proposed model and to explain user behavior from the perspective of link formulation. Results indicate that: (i) new users account for main contributions for the development of co-creation community; (ii) new users prefer to interact high-influence all the time, while old users interchangeably choose preferential attachment or random linking in different time periods, (iii) the initial number of users, the probability for choosing preferential attachment or random attachment has a great influence on the properties of a user interactive network.
期刊介绍:
Computational and Mathematical Organization Theory provides an international forum for interdisciplinary research that combines computation, organizations and society. The goal is to advance the state of science in formal reasoning, analysis, and system building drawing on and encouraging advances in areas at the confluence of social networks, artificial intelligence, complexity, machine learning, sociology, business, political science, economics, and operations research. The papers in this journal will lead to the development of newtheories that explain and predict the behaviour of complex adaptive systems, new computational models and technologies that are responsible to society, business, policy, and law, new methods for integrating data, computational models, analysis and visualization techniques.
Various types of papers and underlying research are welcome. Papers presenting, validating, or applying models and/or computational techniques, new algorithms, dynamic metrics for networks and complex systems and papers comparing, contrasting and docking computational models are strongly encouraged. Both applied and theoretical work is strongly encouraged. The editors encourage theoretical research on fundamental principles of social behaviour such as coordination, cooperation, evolution, and destabilization. The editors encourage applied research representing actual organizational or policy problems that can be addressed using computational tools. Work related to fundamental concepts, corporate, military or intelligence issues are welcome.