Achrekar defends PhD thesis on using social networks to predict flu trends
Achrekar’s PhD research involved online social network (OSN) analysis, with a focus on predicting flu trends and information extraction from messages posted on OSN's. He was utilizing information posted on online social networks such as Twitter and Facebook to help improve the prediction of influenza levels within US population and was tracking of its spread.
He spend three years developing and perfecting an in-house framework called the Social Network-Enabled Flu Trends (SNEFT). The software that uses continuous data-collection mechanism to monitor flu-related messages, extract relevant user demographic and location information, classify messages in real time, and predict the current influenza levels.
Starting 2009, Achrekar tapped into Twitter and Facebook and extracted tens of millions of influenza-related user posts till date, to provide an almost-instantaneous snapshot of current epidemic conditions and building comprehensive mathematical models that improves the estimate of nationwide flu activity.
Achrekar's approach can significantly enhance public health preparedness against influenza and other large-scale pandemics.
For this research, Achrekar was supported with a $200,000 grant from the National Institutes of Health under a Small Business Innovation Research Award.
His results have been presented in various scientific publications:
- His paper “Twitter improves Seasonal Influenza Prediction" at the fifth annual International Conference on Health Informatics, Portugal, February 2012, received the Best Student Paper Award. This is a prestigious and competitive conference with a 9% full-paper acceptance ratio.
- His paper titled “Predicting Flu Trends using Twitter Data” at the International Workshop on Cyber-Physical Networking Systems (CPNS) 2011, in conjunction with IEEE INFOCOM 2011, held in Shanghai, China, April 10–15, 2011, is considered to be a foundational research for flu tracking with OSN data and has received many citations.
- The paper titled “A Spatio-Temporal Approach to the Discovery of Online Social Trends” at the fifth Annual International Conference on Combinatorial Optimization and Applications (COCOA), Zhangjiajie, China in August 2011 provides insights into using online social network data to discover trends in other domains.
- Also “Vision: Towards Real Time Epidemic Vigilance through Online Social Networks” was his first ACM Workshop paper at Mobile Cloud Computing & Services: Social Networks and Beyond (MCS), in conjunction with ACM MobiSys, San Francisco, California, June 2010, that explains the SNEFT architecture for flu tracking and pandemic outburst detection using online social network data.
Dr. Achrekar’s committee included Cindy Chen (Computer Science), Georges Grinstein (Computer Science), Yan Luo (Electrical and Computer Engineering), and Jie Wang (Computer Science).
Harshavardhan (Harsh) Achrekar at his doctoral defense on September 6, 2012.