| With the arrival of Web2.0, Social Networking Sites (SNS) around the world has experienced a rapid development, both of user scale and market size grow explosively. More and more users build or maintain social relationship through SNS, thus SNS has become one of the most popular web applications. As a new media the in the internet age, SNS has great influence on both of the web and realistic society. However, just as other web applications, SNS is facing a series of problems and challenges need to be addressed.Firstly, SNS is facing the problem of losing customers. Since2011, there has been a slowdown in the development of SNS, the user scale of which has shrank greatly. Whether the traditional SNS oriented by games or the emerging microblogs are faced with the challenges of shrinking subscribers, falling stickiness and declining traffic. The biggest appeal of SNS is their huge user scale. The larger the user scale is, the greater the business value of the SNS platform to advertisement and investment is. Therefore, the operators of SNS have to understand users’demands and influencing factors of user’s behavior in the platform, so as to satisfy users’diverse demands through the service improvement, promote users’ social experience, and retain platform user.Secondly, SNS is facing the problem of "free riding". Comparing with the traditional media, the most significant feature of SNS is user generated content (UGC). The amount of the contents in the "public resource pool" symbolizes the liveness of the SNS platform, and represents the core competitiveness and potential development ability in some extent. However, due to the voluntary of user’s contribution, most users choose "free riding", that is, browse the content in the "public resource pool" passively with less or without any contribution,"Free riding" may result in the decrease in the contents of the "public resource pool", which will in turn result in the user churn. To solve the "free riding" problems, operators of SNS have to explore effective incentive mechanism to influence these selfish end users, so as to enhance their content contribution interests, and improve the utility of the whole platform.Thirdly, there are mass low-quality and junk information in the "public resource pool" of the SNS platform. SNS is faced with the problem of mass low-quality and junk information. With the arrival of Web2.0, SNS has experienced a rapid development, and has become one of the main media platforms to get information. Meanwhile, many characteristics of SNS, such as fast information release, quick spread, and fragmented expression, attract more and more user to generate contents and share information. SNS has become a new channel for the public to express interest appeal, and its social influence is enhanced gradually. However, the feature of "self-media" and the widely various users’ quality, especially the existence of "water army", make the SNS platform as the "hardest-hit areas" with many redundant or junk information, which disturbs the normal network order seriously. The existence and spread of mass low-quality information in the "public resource pool" result in the serious waste of network resource, and also influence user experience, lower user’s trust level to the platform, and bring huge loss to the network operators. Therefore, how to guarantee and improve the information quality in the public resource pool has become a challenge for SNS platform.Last but not the least,"inactive" is also a serious problem SNS faced with. Users are the core resource of SNS, interaction between users is the base of the benign development, and the key factor advertisers and investors. The more frequent the interaction between users is, the more business value the SNS has. Content review, as an important interaction behavior, plays a significant role in keeping and improving liveness of SNS. However, in fact, most users are "come soundlessly, and go without any trace". These users log in SNS only to browse content other users generated, but do not interact with others, especially, do not leave comments to the contents they have browsed. Under this situation, users who have contributed content could not get the feedback and support of other users, so their enthusiasm to contribution will be reduced largely, thus the liveness of the whole platform will lower and lower, and the network will become more and more silence. Therefore, how to improve the interaction degree and attract more users to make comments is also a key problem SNS operators faced with.Users are the base of SNS’s business value. High popularity, frequent interaction, high-quality content, can highlight the value of SNS in advertising, the third-party application development, providing value-added services, etc, and also can improve users’stickiness and loyalty. To solve the above mentioned problems SNS faced with, this dissertation makes the following studies.(1) To understand users’demands more clearly and improve user experience, chapter3employs the structure equation model (SEM) to research the influencing factors of SNS users’behavior. Firstly, based on the existing studies, the variables and hypothesizes are proposed, based on which, a theoretical model of influencing factors of SNS users’behavior is established. Then, collects data through questionnaires, employs SPSS18.0and AMOS17.0, and adopts factor analysis and SEM to make an empirical analysis to the theoretical model proposed.Research results show that social relationship, entertainment benefits, functional benefits and direct network externalities are the main factors influencing users’participation level positively, but cross network externality has a negative influence on user’participation level; Additionally, cost-benefit, social relationship, reputation and status are the main factors that affect users’contribution level positively, but direct network externalities and cross network externality have negative effects on user’contribution level.(2) To study the incentive mechanism of improving contribution level of SNS users, chapter4establishes a model of user contribution behavior based on the game theory frame. Through observing the dynamic behavior process of SNS users, study users’"free riding" behavior. Then based on the agent-principle theory, the incentive mechanism of improving contribution level is proposed. According to this incentive mechanism, incentive reward in the form of virtual currency is assigned to users according to their contribution level, thereby, incentive users to contribute content, and improve their time and content contribution level.Research results prove that "free riding" is inevitable. SNS platform doesn’t need to give users additional incentive remuneration under complete information, but need to give them additional incentive remuneration related to their contribution level under incomplete information. The optimal incentive coefficient should increase with the output coefficient of users’contribution, and decrease with the cost coefficient and risk aversion coefficient. The incentive mechanism based on virtual payment, through giving users some incentive rewards related to their contribution level, can encourage them to improve their contribution probability, and solve the problem of "free riding" to some extent.(3) In order to improve the quality of the content users generated in SNS, and prevent users from releasing junk information, chapter5introduces an audit mechanism based on the existing reputation system, thereby puts forward a content quality audit model. With mathematical models and game theory, the influence of different audit probability to users’behavior is analyzed, according to which, the optimal audit mechanism is proposed, so as to provide references for SNS operators to manage the platform scientifically.Research results show that there is a lower audit bound to guide users to exert an effort, and an upper bound to lead users not to exert efforts. When audit probability is higher than the lower bound, all users will choose to contribute, and as audit probability is lower than the upper bound, all users will choose not to work. Audit probability dramatically affects the selfish users’behavior. Under asymmetric review mechanism,"oscillating reputation" and "reverse reputation" will appear. The performance of the reputation system with audit mechanism is superior to the pure reputation without audit system. Under the condition of limited audit resources, and user with high reputation account for a relatively high proportion, SNS platform should review users with low reputation more frequently.(4) To promote users to make comments to the contents they have browsed, chapter6proposes a content recommendation mechanism, through which, users are encouraged to make comments positively. According to this mechanism, the amount and quality of comments are related to the potential content recommendation offered by SNS platform. Only by providing more content comments, users can get content recommendations fit their preferences, thereby lower the time costs consumed in searching information complying with their own interests among the mass information of the "public information pool".The research results show that SNS platform can affect users’ browsing costs through the accuracy of the content recommended, so as to incentive them to provide more comments; Within the SNS system, there is a correlation between users and their friends in a certain social group, and it is possible that users within a social group possess similar interests and preferences.The innovations of this dissertation are as follows:(1) A structure equation model of influencing factors of SNS users’ behavior is proposed and verified. In the process of model establishment, users’participation behaviors are investigated from2dimensions, that is, participation level and contribution level. Furthermore, online time and visit frequency are employed to measure users’participation level, the quality and quantity of content generated are adopted to measure users’ contribution level. Meanwhile, influencing factors of users’participation behaviors are investigated through3dimensions, namely, users themselves, relationship between users and platform environment. Additionally, direct network externality and cross-network externality are introduced into the model to investigate the influence of user amount and advertisements to users’behavior.(2) Based on the frame of game theory, a contribution behavior model of SNS users is established to invested users’behavior. And a virtual payment incentive model is constructed with the agent-principal theory, and the validity of the incentive mechanism is verified by simulation, Many scholars have studied the "free riding" problem and its restrain mechanism in virtual communities. However, there is seldom researches study the reason and probability of users’contribution in SNS with mathematical models. This dissertation constructs a contribution behavior model of SNS users based on the frame of game theory, though investigating users’dynamic behavior process, it is proved that "free riding" are inevitable in the platform of SNS. Research results show that both of the sharing benefits and independent costs are the main reasons for free riding. Meanwhile, agent-principal theory is applied in SNS area for the first time in this dissertation. The virtual payment incentive model for users’contribution is established to study the optimal incentive mechanism for both risk-neutral and risk-aversion users under complete information and incomplete information. Additionally, through dynamical simulation model, the optimal incentive level is obtained, and the individual and overall completion rates of the contribution tasks of SNS are investigated, so that the validity of the proposed incentive mechanism is verified.(3) Introduce audit mechanism into existing reputation system of SNS, and establish an audit mechanism based on users’reputation to incentive users to improve their generated content quality. Existing studies on information quality in virtual communities are focused on the reality of users’comments and the reliability of merchants’commodities information in E-commerce sites, or the behavior of malicious nodes in P2P networks. Generally, existing studies, on the basis of game theory, restrain false information release through investigating the users’ historical behaviors to influence their reputation in future. Reputation system has been applied in SNS widely, however, generally, there is no audit mechanism introduced. The dissertation introduces the audit mechanism into existing reputation system of SNS, and proposes an audit mechanism based on users’reputation to incentive users to improve their generated content quality. Additionally, based on mathematical models and game theory, analyze the influence of different audit probability on users’behavior, according to which, propose the optimal audit mechanism to study the optimal audit resource allocation problem under limited audit resource.(4) Propose a content recommendation mechanism based on users’ reputation to incentive review to browsed contents positively. Interaction between users is the key factor influencing the success of SNS, in which, review of individual users to the contents they have reviewed is a main form of interaction. However, there is no literature to study the incentive mechanism of users’comments. This dissertation introduces content recommendation mechanism to the study of user review incentive mechanism in SNS, and calculates users’reputation value and relevancy between users with users’historical comments and existing comments of the potential contents. A content recommendation mechanism based on reputation is proposed to guide users browse contents they interested with lower costs, so as to incentive users to make more content comments. Through connecting the quality and quantity of users’content comments with the accuracy of the recommended content they received and the time costs they browsed, incentive users to provide more comments, so as to improve the liveness of the platform. Additionally, considering users in a social group may have the similar interests and preferences, the dissertation introduce influence of one’s friends into the reputation value calculation process, and extend the base reputation model to a social reputation model. Taking review records of one’s friends into consideration, a reliable reputation value of a potential content is obtained based on the relevancy between oneself and his/her friends, so as to incentive users to comment more. |
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