Electrical and Computer Engineering ETDs

Publication Date

Spring 5-1-2025

Abstract

The prevalence of Online Social Networks has completely changed how individuals communicate and cooperate. This dissertation explores the integration of intelligent crowdsourcing mechanisms into OSNs, focusing on game theory, reinforcement learn- ing, and social network dynamics to enhance the allocation of tasks, participation by users, and distribution of rewards. It proposes several models that utilize trust- based models, hedonic coalition games, and influencer dynamics for optimization of crowdsourcing. The major challenges to be addressed include task selection, reward distribution, and incentivizing participation, taking into consideration aspects re- lated to social influence, trust, and user engagement. The models so proposed have shown scalability, operational efficiency, and outperform the traditional crowdsourcing methods using simulations and case studies. This work takes up the challenge of integrating OSNs with crowdsourcing and develops solutions to enable users and platforms to cooperatively solve complex tasks in a decentralized and trust-aware manner.

Keywords

Crowdsourcing, Online Social Networks, Game Theory, Reinforcement Learning

Document Type

Dissertation

Language

English

Degree Name

Computer Engineering

Level of Degree

Doctoral

Department Name

Electrical and Computer Engineering

First Committee Member (Chair)

Dr. Eirini Eleni Tsiropoulou

Second Committee Member

Dr. Jim Plusquellic

Third Committee Member

Dr. Xiang Sun

Fourth Committee Member

Dr. Symeon Papavassiliou

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