DocumentCode
3604738
Title
Understanding Sequential User Behavior in Social Computing: To Answer or to Vote?
Author
Yang Gao ; Yan Chen ; Liu, K. J. Ray
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
Volume
2
Issue
3
fYear
2015
Firstpage
112
Lastpage
126
Abstract
Understanding how users participate is of key importance to social computing systems since their value is created from user contributions. In many social computing systems, users decide sequentially whether to participate or not and, if participate, whether to create a piece of content directly, i.e., answering, or to rate existing content, i.e., voting. Moreover, there exists an answering-voting externality as a user´s utility for answering depends on votes received in the future. We present in this paper a game-theoretic model that formulates the sequential decision making of strategic users under the presence of such an answering-voting externality. We prove theoretically the existence and uniqueness of a pure strategy equilibrium. To further understand the equilibrium participation of users, we show that there exist advantages for users with higher abilities and for answering earlier. Therefore, the equilibrium has a threshold structure and the threshold for answering gradually increases as answers accumulate. We further extend our results to a more general setting where users can choose endogenously their efforts for answering. To show the validness of our model, we analyze user behavior data collected from a popular Q&A site Stack Overflow and show that the main qualitative predictions of our model match up with observations made from the data. Finally, we formulate the system designer´s problem and abstract from numerical simulations several design principles that could potentially guide the design of incentive mechanisms for social computing systems in practice.
Keywords
Web sites; decision making; human factors; social sciences computing; Stack Overflow; answering-voting externality; sequential decision making; sequential user behavior; social computing system; strategy equilibrium; threshold structure; Analytical models; Computational modeling; Data models; Games; Numerical models; Predictive models; Social computing; Game theory; Incentives; incentives; social computing; social networks; user generated content (UGC);
fLanguage
English
Journal_Title
Network Science and Engineering, IEEE Transactions on
Publisher
ieee
ISSN
2327-4697
Type
jour
DOI
10.1109/TNSE.2015.2470542
Filename
7210192
Link To Document