Event Information

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Title: Bruno Miguel Tavares Goncalve, Moore Sloan Data Science Fellow - NYU
Sharing: Public
Start Time: Friday February 23, 2018 10:30 AM
End Time: Friday February 23, 2018 11:30 AM
Location: Luddy Hall, Room 1106
Contact: Ying Ding
Url: http://data-science-colloq.soic.indiana.edu/
Category: Event
Free/Busy: busy
Description:

Data Science Invited Talk Series

 

Speaker: Bruno Goncalves, Moore Sloan Data Science Fellow – NYU

Where: Luddy Hall, Room 1106

When:  Friday - February 23, 2018 10:30 AM

Webinar Link: https://iu.zoom.us/j/607325285

 

Topic: Spatio temporal analysis of Language use.

Abstract: The advent of large scale online social services coupled with the dissemination of affordable GPS enabled smartphones resulted in the accumulation of massive amounts of data documenting our individual and social behavior. Using large data sets from source such as Twitter, Wikipedia, Google Books and others we will present several recent results on how languages are used across both time and space.

In particular, we will analyze the role of multilinguals in Social Networks and how language dialects can be defined empirically based on the way a language is used in the real world. Finally, we will also analyze how English usage changes from place to place and over time and how languages can be used to identify communities within the urban environment.

 

Bio: Bruno Gonçalves is a Data Science fellow at NYU's Center for Data Science while on leave from a tenured faculty position at Aix-Marseille Université. He has a strong expertise in using large scale datasets for the analysis of human behavior. After completing his joint PhD in Physics, MSc in C.S. at Emory University in Atlanta, GA in 2008 he joined the Center for Complex Networks and Systems Research at Indiana University as a Research Associate. From September 2011 until August 2012 he was an Associate Research Scientist at the Laboratory for the Modeling of Biological and Technical Systems at Northeastern University. Since 2008 he has been pursuing the use of Data Science and Machine Learning to study human behavior. By processing and analyzing large datasets from Twitter, Wikipedia, web access logs, and Yahoo! Meme he studied how we can observe both large scale and individual human behavior in an obtrusive and widespread manner. The main applications have been to the study of Computational Linguistics, Information Diffusion, Behavioral Change and Epidemic Spreading. He is the author of 60+ publications with over 5200+ Google Scholar citations and an h-index of 30. In 2015 he was awarded the Complex Systems Society's 2015 Junior Scientific Award for "outstanding contributions in Complex Systems Science" and he is the editor of the book Social Phenomena: From Data Analysis to Models (Springer, 2015).

Contact Email: dingying@indiana.edu
More Contact Info: datasci@indiana.edu
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