Social, Emotional, and Cognitive Bases of Communication: New Analytic Approaches

Saturday, 14 February 2015: 1:30 PM-4:30 PM
Room LL21B (San Jose Convention Center)
Large-scale datasets -- such as linguistic corpora collected from digital social media or large datasets compiled from human behavioral measures -- provide records of linguistic and nonlinguistic communication within and between individuals and groups. These new resources have inspired the adaptation of new quantitative analyses and measures, some of which were previously more typical of computer scientists, mathematicians, and physicists (information theory) and of psychologists and linguists (word clouds, hierarchical clustering, time series). Further, the technology itself is being transformed to meet not only functional needs of organizing and visualizing data but also the social and emotional aspects of communicating. These innovative lines of inquiry attest to the mutual influence of technology and behavior, and the transformation that ensues as disciplines come in contact. This session brings together a group of psychologists, linguists, and computer scientists, all of whom work on communication in dialogue or in spontaneous or composed text or speech but who differ in aspects of behavior they measure and in the techniques they use to organize, visualize, and analyze large datasets. Presenters will explore a range of questions and share analytic approaches to the study of language and communication that innovative technologies now permit.
Laurie Beth Feldman, University at Albany
Judith F. Kroll, Pennsylvania State University and Cecilia Aragon, University of Washington
Laurie Beth Feldman, University at Albany
Judith F. Kroll, Pennsylvania State University
Cecilia Aragon, University of Washington
Emotion in Informal Text Communication
Munmun De Choudhury, Georgia Institute of Technology
Online Social Dynamics and Emotional Wellbeing
Fermın Moscoso del Prado Martin, University of California
Measuring Conversational Alignment
Patrick Wong, Chinese University of Hong Kong
Neural Efficiency and Language Learning
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