School of Computer Science
Technical Workshop Series: NLP and Social Networks: Exploring Social Network Analysis (SNA)
Presenter: Soroush Ziaeinejad
Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
"Exploring the Intersection of Natural Language Processing and Social Network Analysis (SNA)" is a dynamic workshop uncovering the synergy between NLP and social networks. Covering graph theory basics, community detection, and influence analysis, it seamlessly integrates NLP for powerful text analysis insights. Participants will gain practical knowledge to decipher the intricacies of social structures, fostering a nuanced understanding of the symbiotic relationship between language processing and the dynamics of social networks. The learning objectives/outcomes for this workshop are multifaceted. Participants will acquire a foundational understanding of Social Network Analysis, including graph theory fundamentals, community detection, and influence analysis. The integration of Natural Language Processing techniques for text analysis will be a key focus, allowing participants to gain insights into the intricate dynamics of online interactions. Through hands-on activities and case studies, attendees will develop practical skills in applying SNA methodologies, enhancing their ability to analyze and interpret social structures. Additionally, ethical considerations in the context of SNA will be addressed, emphasizing responsible research practices. The overarching goal is to equip participants with a comprehensive skill set, deepening their understanding of social networks and fostering analytical proficiency in this dynamic field.
- Introduction to NLP and Social Network Analysis (SNA)
- Graph Theory Fundamentals
- Analyzing Social Networks
- Integrating NLP in Social Networks
- Applications and Case Studies
- Hands-on Activity
- Conclusion and Q&A
Basic knowledge of Python and mathematics
Soroush is a Ph.D. student and research assistant at the School of Computer Science. His main research area is Natural Language Processing and Information Retrieval on social networks.