[Colloquium] CSS Presents Brendan O'Connor, Friday 11/16

[Ninfa Mayorga]

Dear Colleagues,

The Computational Social Sciences workshop is excited to host Brendan O'Connor, a doctoral student in Carnegie Mellon University's Machine Learning Department, this Friday from 2-3:00pm in Searle 240a.  Brendan will be presenting "A Framework for Social Data Analysis of Text," a general framework for computational content analysis which synthesizes his numerous projects on sentiment analysis, lexical variation, and online censorship.  Below, you will find Brendan's full abstract and bio below. Hope to see you there!

Sincerely,
Jason Radford


“A Framework for Social Data Analysis of Text”
Friday 2-3:00pm
Searle 240a

What can text analysis tell us about society? Enormous corpora of news, historical documents, books, and social media encode ideas, beliefs, and culture. While manual content analysis is a useful and established social science method, interest in automated text analysis has exploded in recent years, since it scales to massive data sets, and can assist in discovering patterns and themes.

I will present several case studies of using social media text analysis as a measurement instrument for social phenomena: sentiment analysis as a correlate of public opinion polls, geographic lexical variation as data for sociolinguistics, and characterization of Chinese online censorship (time permitting). These examples, and other related work, suggest that "text-as-data" analysis techniques have wide variation in their computational/statistical complexity and amount of domain knowledge. Many methods, from word statistics to sentiment lexicons to document classifiers to topic models, can be unified as "weighted lexicon" corpus analysis tools across these spectrums, supporting both exploratory and confirmatory text data analysis.

BIO:
Brendan O'Connor (http://brenocon.com/) is a Ph.D. Student at Carnegie Mellon University's Machine Learning Department, advised by Noah Smith. He is interested in machine learning and natural language processing, especially when informed by or applied to the social sciences. He has interned on the Facebook Data Science team and worked on crowdsourcing at Crowdflower / Dolores Labs and "semantic" search at Powerset. His undergraduate degree was Symbolic Systems.

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