Adele Lu Jia defends her PhD thesis on incentives in p2p networks

Adele Lu Jia successfully defended her PhD thesis at Delft University of Technology,

Online Networks as Societies: User Behaviors and Contribution Incentives

by Adele Lu Jia

Online networks like Facebook and BitTorrent have become popular and powerful infrastructures for users to communicate, to interact, and to share social lives with each other. These networks often rely on the cooperation and the contribution of their users. Nevertheless, users in online networks are often found to be selfish, lazy, or even ma- licious, rather than cooperative, and therefore need to be incentivized for contributions. To date, great effort has been put into designing effective contribution incentive policies, which range from barter schemes to monetary schemes. In this thesis, we conduct an analysis of user behaviors and contribution incentives in online networks. We approach online networks as both computer systems and societies, hoping that this approach will, on the one hand, motivate computer scientists to think about the similarities between their artificial computer systems and the natural world, and on the other hand, help people outside the field understand online networks more smoothly.

To summarize, in this thesis we provide theoretical and practical insights into the correlation between user behaviors and contribution incentives in online networks. We demonstrate user behaviors and their consequences at both the system and the individual level, we analyze barter schemes and their limitations in incentivizing users to contribute, we evaluate monetary schemes and their risks in causing the collapse of the entire system, and we examine user interactions and their implications in inferring user relationships. Above all, unlike the offline human society that has evolved for thousands of years, online networks only emerged two decades ago and are still in a primitive state. Yet with their ever-improving technologies we have already obtained many exciting results. This points the way to a promising future for the study of online networks, not only in analyzing online behaviors, but also in cross reference with offline societies.

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