ABOUT

they/them | tmasis@cs.umass.edu | Semantic Scholar | LinkedIn | CV

I am a PhD student in Computer Science at the University of Massachusetts Amherst, advised by Brendan O'Connor and supported by an NSF Graduate Research Fellowship. I'm a member of the SLANG Lab and the larger UMass NLP group.

My research is in the domain of natural language processing and computational social science. In particular, I'm interested in using computational methods to investigate linguistic or social phenomena, especially ones relevant to marginalized groups, in text data.

I also live with a chronic pain condition, which significantly impacts my life as well as my ability to work. Here are some resources on disability and why health/ability to be productive is morally neutral:
- What Can a Body Do?: How We Meet the Built World
- Disfigured: On Fairy Tales, Disability, and Making Space
- Strategies for change: thriving as a disabled individual in STEMM
- The Sound of a Wild Snail Eating
- Illness as Metaphor and AIDS and Its Metaphors
- The Capacity Contract: Intellectual Disability and the Question of Citizenship
- How to Keep House While Drowning: A Gentle Approach to Cleaning and Organizing

RESEARCH

Where on Earth Do Users Say They Are?: Geo-Entity Linking for Noisy Multilingual User Input.
Tessa Masis and Brendan O'Connor.
IC2S2, 2024. [abstract] [slides]
NLP+CSS Workshop at NAACL, 2024. [paper] [poster]

The Online #StopAsianHate Movement: More Global and BTS-Driven Than You'd Think.
Tessa Masis, Zhangqi Duan, Weiai Xu, Jonathan Corpus Ong, Ethan Zuckerman, Jane Pyo, and Brendan O'Connor.
TADA, 2023. [abstract] [poster]

Investigating Morphosyntactic Variation in African American English on Twitter.
Tessa Masis, Chloe Eggleston, Lisa Green, Taylor Jones, Meghan Armstrong, and Brendan O'Connor.
SCiL, 2023. [abstract] [slides]
IC2S2, 2023. [abstract] [slides]

A large-scale Twitter-based exploration of morphosyntactic geographic variation in African American English.
Tessa Masis, Chloe Eggleston, Anissa Neal, Lisa Green, and Brendan O'Connor.
NWAV50, 2022. [abstract] [slides]

Corpus-Guided Contrast Sets for Morphosyntactic Feature Detection in Low-Resource English Varieties.
Tessa Masis, Anissa Neal, Lisa Green, and Brendan O'Connor.
Field Matters Workshop at COLING, 2022. [paper] [github] [poster] [slides]

ProSPer: Probing Human and Neural Network Language Model Understanding of Spatial Perspective.
Tessa Masis and Carolyn Jane Anderson.
BlackboxNLP Workshop at EMNLP, 2021. [paper] [poster]

Can neural network language models learn spatial perspective from text alone?
Carolyn Jane Anderson and Tessa Masis.
Bridging AI and Cognitive Science (BAICS) Workshop at ICLR, 2020. [paper]

The Poetics of Gender Devaluation in Homeric Heroism.
Tessa Masis.
Scholarship for Undergraduate Literary Studies conference, 2020. [paper]

TEACHING

Spring 2022:
COMPSCI 220 Programming Methodology (Teaching Assistant)

Fall 2020:
Developed culturally sustaining assessment tools (CSAT) for computational thinking in early elementary students (in collaboration with PIs of related NSF-funded research project)

Fall 2019:
COMPSCI 220 Programming Methodology (Undergraduate Teaching Assistant)