Capturing Digital Signals for Lifestyle Health Research - Yelena Mejova (ISI Foundation, Turin)


The scale and complexity of the traces of human behavior captured on the web has been a useful resource for tracking disease, pushing the lag of conventional health tracking to more real-time "now-casting". These signals provide a rich source of information about the context of people's health conditions, revealing their cultural, social, and personal attitudes and behaviors, making social media data especially useful for understanding lifestyle diseases, such as obesity and diabetes -- conditions that claim more lives than infectious diseases worldwide. This talk will discuss the latest findings in lifestyle disease tracking via large social media collections encompassing population and individual scales. *Bio*: Yelena Mejova is a Research Leader at the ISI Foundation in Turin, Italy, a part of the Digital Epidemiology group (previously, a scientist at the Qatar Computing Research Institute, Qatar). Specializing in social media analysis and mining, her work concerns the quantification of health and wellbeing signals in social media, as well as tracking of social phenomena, including politics and news consumption. She co-edited a volume on the use of Twitter for social science in "Twitter: A Digital Socioscope", and a special issue of Social Science Computer Review on Quantifying Politics Using Online Data. Previously, as a postdoctoral member of the Web Mining team at Yahoo! Research Barcelona, Yelena participated in the Linguistically Motivated Semantic Aggregation Engines (LiMoSINe) EU project. Also, Yelena has published widely on sentiment analysis and its application to social media and political speech.

13/10/2018



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