Colloquium Series Presentation by Dr. Ebrahim Bagheri:"Computational Social Semantics for Mining Actionable Insights"

The influence of social media platforms on many aspects of our personal and societal lives has given rise to a host of computational methods that analyze social data. In this talk, I will motivate the need for computational semantics, i.e., automated sense making of social user generated content, in order to enable a deeper analysis of social content. I will present my group's approach to grounding social content in semantics despite their challenging characteristics including being antigrammatical, noisy and lacking in context. I will then show how capturing the semantics of social content can lead to a range of methods for micro (user level) and macro (community-level) analysis of social media content, as well as allowing for performing natural experiments through observational studies. I will provide impactful applications of our work in the healthcare domain such as maternal mental health and knowledge synthesis in the medical literature.

 

Ebrahim Bagheri is an Associate Professor in the Department of Electrical, Computer and Biomedical Engineering at Ryerson University. He holds a Canada Research Chair (Tier II) in Software and Semantic Computing as well as an NSERC Industrial Research Chair in Social Media Analytics. He works on computational models for the semantic analysis of highly unstructured textual content in order to interpret the meaning behind surface-level human communication, leading to highly efficient information processing and management tools and techniques. His publications have appeared in top-tier venues such as IP&M, Information Retrieval Journal, CIKM, WSDM, and ECIR. Ebrahim has been awarded the NSERC Synergy Award for Innovation for his long-standing impactful university-industry collaborations, as well as the Professional Engineer's Ontario Young Engineer of the Year award for achievements not only in career, but also in community and professional participation.