Su Lin Blodgett

About me

Publications

Miscellaneous

Contact

I am a fourth-year M.S./Ph.D student in computer science at UMass Amherst working in the Statistical Social Language Analysis Lab, advised by Brendan O'Connor. I am interested in using statistical text analysis to answer social science, particularly sociolinguistic, questions. Currently, I am working on developing models to identify dialectal variation on social media.

I am also interested in developing fair, robust tools for computational social science.

I am supported by the NSF Graduate Research Fellowship. I received my B.A. in mathematics from Wellesley College.

Email: blodgett [at] cs [dot] umass [dot] edu

In this interview for the UMass Women in Science video series, I briefly describe my work and my journey to computer science.

2018

Twitter Universal Dependency Parsing for African-American and Mainstream American English. Su Lin Blodgett, Johnny Tian-Zheng Wei, and Brendan O'Connor. Annual Meeting of the Association for Computational Linguistics (ACL). July 2018. [pdf] [data]

Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses. Katherine Keith, Su Lin Blodgett, and Brendan O'Connor. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). June 2018. [pdf]

2017

A Dataset and Classifier for Recognizing Social Media English. Su Lin Blodgett, Johnny Tian-Zheng Wei, and Brendan O'Connor. 3rd Workshop on Noisy User-Generated Text (W-NUT), EMNLP. September 2017. W-NUT Best Paper Award. [pdf] [data]

Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English. Su Lin Blodgett and Brendan O'Connor. Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) Workshop, KDD. August 2017. [pdf] [data]

2016

Demographic Dialectal Variation in Social Media: A Case Study of African-American English. Su Lin Blodgett, Lisa Green, and Brendan O'Connor. Conference on Empirical Methods in Natural Language Processing (EMNLP). November 2016. [pdf] [data]

Visualizing Textual Models with In-Text and Word-as-Pixel Highlighting. Abram Handler, Su Lin Blodgett, and Brendan O'Connor. Proceedings of the Workshop on Human Interpretability in Machine Learning (WHI), ICML. June 2016. [pdf]