Event Status
Scheduled
Online social networks like Facebook, Twitter, Quora, etc have greatly influenced our social lives. This effect extends to economic and political realms, where social networks have become the best media for targeted campaigns of products and political ideas. From these perspectives as well as from the perspective of social sciences understanding the evolution of opinions and its effect on societies is of great importance. In the first part of this proposal we study opinion evolution in a social network. We propose a new model of opinion dynamics called stochastic bounded confidence opinion dynamics that generalizes the well known bounded confidence opinion dynamics proposed by Deffuant et al. (2000) by capturing stochastic opinion dependent opinion exchange, noise in opinion exchange and intrinsic beliefs of social agents. We theoretically characterize the conditions under which such a dynamic is stable in the sense that the opinion differences are finite. Analytically and in simulations we observe phenomena that relate well to real societies.
With the advent of crowdsourcing platforms like Amazon Mechanical Turk, oDesk, etc the perception about an online user as only a potential buyer or consumer has changed. These platforms have enabled the online users to earn money by performing tasks at their convenience. Most crowdsourcing platforms are uncontrolled and offer freedom to customers and freelancers to choose each other. This works well for unskilled jobs (e.g., image classification) with no specific quality requirement since freelancers are functionally identical. For skilled jobs (e.g., software development) with specific quality requirements, however, this does not ensure that the maximum number of job requests is satisfied. In the second part of this proposal we determine the capacity of freelance markets, in terms of maximum satisfied job requests, and propose centralized schemes that achieve capacity. To ensure decentralized operation and freedom of choice for customers and freelancers, we propose simple schemes compatible with the operation of current crowdsourcing platforms that approximately achieve capacity.
As a future work, we propose to study the problem of inferring opinions of social agents by observing interactions between them.
Event Details
Date and Time
Oct. 8, 2014, All Day