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APS Virtual Poster Showcase

Current Directions of Natural Language Processing in Social and Behavioral Sciences

Friday, May 22, 2020 · Virtual

Oral · Methodology

Natural language processing (NLP) is a powerful technique for measuring psychological features in big, text-based data. This symposium brings together five researchers who apply NLP in different facets of social and behavioral science. Current methodological progress and issues pertaining to machine learning strategies used in NLP will be discussed.

Chairs & Discussants

  • Manyu LiChair
    University of Louisiana at Lafayette
  • Ryan BoydCoChair
    Lancaster University
  • Ryan BoydDiscussant
    Lancaster University

Presentations

  1. Unsupervised Text Classification and Sentiment Analysis Application in Large-Scale National Text DataManyu Li
  2. How Do Group Members Respond to a Change-Agent Newcomer’s Use of Integrating “We” Pronouns Versus Differentiating “I” and “You” Pronouns?Aimee Kane, Floor Rink
  3. Bound in Hatred: A Multi-Methodological Investigation of Morality's Role in Acts of HateJoe Hoover, Morteza Dehghani
  4. Natural Language Processing of Complex Language: The Tension between Machine Learning and Human Evaluation Approaches to Automating Integrative ComplexityLucian Conway, Shannon Houck, Alivia Zubrod, Linus Chan, Kathrene Conway