Tech Tuesday Talks is a monthly seminar series bringing together researchers from across the USC campus who share interest in technology-assisted health promotion and disease prevention interventions and research. The series presents a forum to learn about one another’s work, spark collaborations as well as to introduce students to the ongoing research conducted on the USC campus which incorporates technology in health promotion. All interested faculty and students are invited to attend. The event is free and open to the public.
Tech Tuesday Talks are presented on the fourth Tuesday of the month in Discovery I Building, Room 140 at noon. Lunch will be available for the first 20 arrivals and you may also bring your own lunch with you. For more information email firstname.lastname@example.org.
Tuesday - April 23 - Noon
915 Greene Street, Discovery 1, Room 140
Social Computing and Health Informatics: Mining Big Twitter Data in regard to Diabetes, Diet, Exercise, and Obesity
Amir Karami, PhD
Assistant Professor, School of Library and Information Science
Social media provide a platform for users to express their opinions and share information. Understanding public health opinions on social media, such as Twitter, offers insights into the thinking of the general public on important health issues (e.g., diabetes, diet, exercise, and obesity). The goal of this research is to analyze the characteristics of public opinion about diabetes, diet, exercise, and obesity as expressed on Twitter. A multi-component semantic and linguistic framework was developed to collect Twitter data, discover topics of interest within diabetes, diet, exercise, and obesity, and analyze the topics.
Amir Karami, PhD, is an Assistant Professor in the School of Library and Information Science, as well as Faculty Associate for the South Carolina SmartState Center for Healthcare in the Arnold School of Public Health. He received his PhD in Information Systems from the University of Maryland, Baltimore County. Dr. Karami’s work focuses on big data and text mining, health and medical informatics, and social media analysis to understand various health-related behaviors and outcomes.