- Classification and Analysis of Neologisms Produced by Learners of Spanish: Effects of Proficiency and Task. *Shira Wein. Association for Computational Linguistics (ACL), Widening NLP (WiNLP) Workshop 2020. [Video] [ACL Anthology / Bibtex]
- A Human Evaluation of AMR-to-English Generation Systems. Emma Manning, *Shira Wein, Nathan Schneider. arXiv preprint.
- Sentiment Analysis on Translated Works: Explaining the Differences Between Linguistic Analysis of a Text and its Computational Sentiment. *Shira Wein, 2019. Unpublished senior thesis, Departments of Computer Science and Spanish, Lafayette College, Easton, PA. [Winner of Barge Oratorical Prize – Best Oral Defense of Honors Thesis]
- Crowdsourcing Preposition Supersense Annotation with Paraphrase Judgments. Luke Gessler, *Shira Wein, Nathan Schneider. MASC-SLL 2020.
- Referenceless Evaluation of Natural Language Generation from Meaning Representations. Emma Manning, *Shira Wein, Nathan Schneider. MASC-SLL 2020.
- Tame Your Computer: Using the Command Line. *Shira Wein. Lafayette College ACM Fall Lunch & Learn Series 2017.
- The Grand Tour as Spatial Narrative: Story Maps in the Liberal Arts Study Abroad Curriculum. Markus Dubischar, Jason Simms, *Shira Wein. Conference for Blended Learning in the Liberal Arts (Bryn Mawr College) 2017.
- Integrating Digital Humanities into Computer Science. Amir Sadovnik, *Shira Wein, Wassim Gharbi. Skillman Library Digital Humanities in the Classroom (Lafayette College) 2016.
- The Role of Women in Computing. *Shira Wein. TEDxLaf Fall Conference 2015.
GRADUATE RESEARCH ASSISTANT, GEORGETOWN UNIVERSITY
Current project: Crowdsourcing Preposition Supersense Annotation
August 2019 to Present
Working with Nathan Schneider (and collaborators in NERT) on various research projects in natural language processing and computational linguistics. Research includes evaluation of natural language generation systems and crowdsourcing tasks to expedite annotation.
UNDERGRADUATE SENIOR HONORS THESIS
Sentiment Analysis on Translated Works: Explaining differences between linguistic analysis of a text and its computational sentiment
May 2018 to May 2019
Presents a novel approach for literary analysts to utilize computational sentiment analysis in metacognition, as well as a tool to provide transparency for deep neural networks for lay users. Co-advised by Joann Ordille and Michelle Geoffrion-Vinci.
EXCEL RESEARCH, LAFAYETTE COLLEGE COMPUTER SCIENCE DEPARTMENT
Modeling Cell Signal Cascades
May to August 2016
Worked with a team of biologists to develop a modeling system to analyze the biological process of signaling cascades. Supervised by C.W. Liew.