SLANG Lab: Statistical Social Language Analysis
What can statistical text analysis tell us about society? The SLANG Lab (Statistical Social Language Analysis, directed by Prof. Brendan O'Connor) develops natural language processing, machine learning, and data analysis tools to improve scientific investigation about political and social phenomena. For example, we analyze political events in news articles, and sentiment in social media.
Current Members
- Brendan O'Connor (Associate Professor)
- Katherine Keith (PhD student)
- Ankita Gupta (PhD student)
- Tessa Masis (PhD student)
Projects
- IndiaPoliceEvents Corpus
- Document Prevalence Estimation
- African-American English on Twitter
- Police Killings Extraction
- Rookie: Exploring News Archives
- phrasemachine software
Alumni
PhD Students
- Su Lin Blodgett (PhD, 2020) Postdoctoral Researcher, MSR
- Abram Handler (PhD, 2021) Instructor, University of Colorado Boulder
Undergraduate
- Michael Pinkham, Columbia, REU Summer 2016
- Benjamin Tseytlin, UMass, B.S. '16, Honors
- Khanh Nguyen, UMass, B.S. '15, Honors (→ U. Maryland CS PhD program)
- Cara Magliozzi, UMass, B.S. '15 (→ Google)
- Joshua McDuffie, UMass, B.S. '15
About
The SLANG Lab is part of the College of Information and Computer Sciences at the University of Massachusetts, Amherst. We are affiliated with groups for data science (CDS, MLDS), information retrieval (CIIR), linguistics / cognitive science (CogSci), and computational social science (CSSI) here at UMass.Support
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