Event Information

Title: Stephen Kobourov, University of Arizona
Sharing: Public
Start Time: Friday October 27, 2017 01:30 PM
End Time: Friday October 27, 2017 02:30 PM
Location: Lindley Hall  
Contact: Katy Borner
Url: http://data-science-colloq.soic.indiana.edu/
Free/Busy: busy

Data Science Invited Talk Series


Speaker: Stephen Kobourov, Professor of Computer Science – University of Arizona

Where: Lindley Hall, Room 102

When:  Friday - October 27, 2017 1:30 PM

Webinar Link: https://iu.zoom.us/j/149995508


Topic: Analyzing the Language of Food on Social Media

Abstract: In this lecture, we investigate the predictive power behind the language of food on social media from a collected corpus of over three million food-related posts from Twitter. Using this, we will demonstrate that many latent population characteristics can be directly predicted from this data:
overweight rate, diabetes rate, and political leaning. We analyze which textual features have most predictive power for these datasets, providing insight into the connections between the language of food, geographic locale, and community characteristics. Lastly, we describe and demonstrate an online system for real-time query and visualization of the dataset. Visualization tools, such as geo-referenced heatmaps, semantics-preserving wordclouds, and temporal histograms allow us to discover more complex, global patterns mirrored in the language of food.

Bio: Stephen Kobourov is a Professor of Computer Science at the University of Arizona. He completed BS degrees in Mathematics and Computer Science at Dartmouth College in 1995, and a PhD in Computer Science at Johns Hopkins University in 2000. He has worked as a Research
Scientist at AT&T Research Labs, and is a Humboldt Fellow at the University of Tübingen in Germany as well as a Distinguished Fulbright Chair at Charles University in Prague.


Contact Email: katy@indiana.edu
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