Exploring Pragmatic Characteristics of Security-Related Conversations Jan 2019 — Present
  PI(s): Andrew Meneely, Ph.D.
Collection, annotation, and analysis of a dataset of over 400,000 bug reports containing over 2,000,000 developer comments from the Chromium project. Focus on pragmatic characteristics of security-related natural language: formality, informativeness, implicature, politeness, and uncertainty detection.
Talking Security: Linguistic Characteristics of Cybersecurity Conversations Aug 2018 — Jan 2019
  PI(s): Andrew Meneely, Ph.D.
Collection, annotation, and analysis of podcast conversations encompassing four categories of subject matter: (1) Computing, Security; (2) Computing, Non-Security; (3) Non-Computing, Security; (4) Non-Computing, Non-Security. Analyses include politeness, formality, informativeness, implicature, syntactic complexity, and uncertainty detection.
Analyzing Discourse Patterns in Code Review Conversations Jan 2017 — Aug 2018
  PI(s): Andrew Meneely, Ph.D.; Emily Prud'hommeaux, Ph.D.; Cecilia O. Alm, Ph.D.; Josephine Wolff, Ph.D.
Applied natural language processing techniques to a dataset of almost 800,00 code reviews from the Chromium project during an exploratory analysis of discourse between software developers. Analyses included inquisitiveness, sentiment analysis, politeness, formality, propositional density, uncertainty detection, and syntactic complexity.
Adapting the Case Study Model for Learning of Linguistic Concepts Aug 2015 — Dec 2016
  PI(s): Cecilia O. Alm, Ph.D.; Emily Prud'hommeaux, Ph.D.
Developed a set of distinct case study activities using genuine linguistic datasets to aid student learning and engagement in introductory linguistics classes. Enhanced the visualization capabilities of an existing web application, Linguine, that aided in the analysis of the case study data.
Computational Analysis of Trajectories of Linguistic Development in Autism May 2015 — Aug 2015
  PI(s): Emily Prud'hommeaux, Ph.D.; Cecilia O. Alm, Ph.D.
Adapted natural language processing techniques to a corpus of speech transcriptions collected from college-aged males with and without autism spectrum disorder. Examined the trajectories of linguistic development in autism through analysis of various syntactic-, semantic-, and discourse-based metrics.