Electrical and Computer Engineering ETDs
Publication Date
Spring 4-11-2023
Abstract
This thesis addresses the challenge of user recruitment by various competing marketing agencies (MAs) in Online Social Networks. A labor economics approach, following the principles of contract theory, is devised to enable MAs to reveal the potential of each participating user to contribute a personalized level of quality and quantity of information to the crowdsourcing process. The MAs objective is to maximize their personal benefit, i.e., total utility obtained, given its budget. The latter optimization problem is formulated as a Generalized Colonel Blotto (GCB) game among the MAs, where each MA aims at incentivizing each user to report its information. A Pure Nash Equilibrium (PNE) is determined resulting in the optimal rewards each MA should provide to each user. The performance evaluation of the proposed approach is achieved via modeling and simulation, and numerical results are presented to reveal the benefits of the proposed crowdsourcing model under different scenarios.
Keywords
Labor Economics, Colonel Blotto Game, Social Networks, Crowdsourcing, Optimization, Game Theoretic
Document Type
Thesis
Language
English
Degree Name
Computer Engineering
Level of Degree
Masters
Department Name
Electrical and Computer Engineering
First Committee Member (Chair)
Dr. Eirini Eleni Tsiropoulou
Second Committee Member
Dr. Jim Plusquellic
Third Committee Member
Dr. Symeon Papavassiliou
Recommended Citation
Kubiak, Natasha S.. "Network Economics-based Crowdsourcing in Online Social Networks." (2023). https://digitalrepository.unm.edu/ece_etds/583