Professor of Computer Science, Elon University.
Specialist Research Areas: Database Systems, Data Mining, Network Analysis, Cybersecurity, Online Communities
Megan Squire is a professor in the department of Computer Science at Elon University (USA). She earned a Ph.D. and M.S. in computer science at Nova Southeastern University and B.A. in art history and public policy from The College of William and Mary. She applies data science techniques to the study of online communities, specializing in the creation of infrastructure to support collection, curation, and federation of large amounts of metadata, textual data, and image data to further understanding about how online communities work.
Her recent projects include network analysis of radical right extremist groups on social media. Dr. Squire’s focus is on collecting data from across the social media landscape, cleaning and organizing it, and then mining it for interesting patterns. For example, network analysis, image analysis, and text mining techniques can help researchers understand membership trends and the radicalization practices of extremist groups across multiple ideologies. Dr. Squire also uses text mining and machine learning techniques to identify individuals as they move across different social media platforms.
Dr. Squire is the author of two books on data cleaning and data mining, and over 35 peer-reviewed articles and book chapters, including several Best Paper awards. She has earned nearly $500,000 in external competitive grant funding from the National Science Foundation, the Computing Research Association, and in-kind equipment and computing time donations from industry partners. She is an active participant and leader of numerous program committees for conferences and journal editorial boards. In 2017 she was named the Elon University Distinguished Scholar.
Specialist research areas:
Database systems, data mining, data collection, big data, social informatics, network analysis, text analysis, data privacy, cybersecurity, illicit networks, online communities.