Modeling User Interaction on Social Media at a Microscopic Level

Social network concept

The ease of accessibility and reach make online social networks(OSN) a strategic tool that businesses, interest groups, politicians and journalists often employ during crises and disasters. The diversity of users, ideas, participation style, community involvement, and volume of posts are some of the unique attributes of OSN users that appear to influence information processing and the decision-making process of gathering information, identifying alternatives and weighing the evidence. 

In this research, we are looking at understanding and modeling the features that impact information diffusion, opinion formation, and decision-making in OSN. This project integrates the state-of-the-art research on social media communication into a comprehensive, attribute-based, learnable valid model for influence in social networks. The model will be essential in tracking the node-to-node influence capabilities, and ultimately the influence of a node in his network. 

Implicit Crowdsourcing for Identifying Abusive Behavior in Online Social Networks

 

Abiola-Osho-headshot.jpg

Abiola is a PhD student who joined the PITS lab in 2017. Abiola earned a bachelor's degree in Computer Engineering from Olabisi Onabanjo University, Nigeria and a master's in Computer science from The University of Ibadan, Nigeria. She has over 3 years' industry experience in Networking and IT service management.

PhD Student

Abiola Osho

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Colin is an undergraduate student pursuing a bachelor's degree in computer science. He is currently a sophomore, and he joined the PITS lab in 2018. His interests include cyber security and data science.

Undergraduate Student

Colin Goodman

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