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
project. Focus on pragmatic characteristics of security-related natural language: formality,
informativeness, implicature, politeness, and uncertainty detection.
Quantifying Disaster Risk Reduction Geographic Information Capacity
May 2019 — Aug 2019
PI(s): Brian Tomaszewski, Ph.D.; Klaus Greve, Ph.D.; Jörg Szarzynski, Ph.D.
This International Research Experience for Students
is focused on quantifying disaster risk reduction geographic information capacities. Each year, a cohort of
five U.S. graduate students from the Rochester Institute of Technology (RIT) will participate in a ten-week
summer research experience with collaborators at the United Nations University Institute for Environment and
Human Security (UNU-EHS) and the University of Bonn (UBonn) - both located in Bonn, Germany. Highlights of
collaborative activities include student access to and learning from UNU-EHS, UBonn, and other international
disaster risk reduction experts, student research training activities, spatial data set acquisition, and
access to international scientific networks only available in Bonn.
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
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
project during an exploratory analysis of discourse between software developers. Analyses included
inquisitiveness, sentiment analysis, politeness, formality, propositional density, uncertainty detection, and
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
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.