How We Do Things With Words: Analyzing Text as Social and Cultural Data
Year: 2020
Type: article
Abstract: In this article we describe our experiences with computational text analysis involving rich social and cultural concepts. We hope to achieve three primary goals. First, we aim to shed light on thorny issues not always at the forefront of discussions about computational text analysis methods. Second, we hope to provide a set of key questions that can guide work in this area. Our guidance is based on our own experiences and is therefore inherently imperfect. Still, given our diversity of disciplinary backgrounds and research practices, we hope to capture a range of ideas and identify commonalities that resonate for many. This leads to our final goal: to help promote interdisciplinary collaborations. Interdisciplinary insights and partnerships are essential for realizing the full potential of any computational text analysis involving social and cultural concepts, and the more we bridge these divides, the more fruitful we believe our work will be.
Authors: Nguyen, Dong, Liakata, Maria, Dedeo, Simon, Eisenstein, Jacob, Mimno, David, Tromble, Rebekah, Winters, Jane, Sub Natural Language Processing, Natural Language Processing
Institutions: Utrecht University, The Alan Turing Institute, University of Edinburgh, Queen Mary University of London, University of Warwick, Santa Fe Institute, Carnegie Mellon University, Georgia Institute of Technology, Cornell University, George Washington University, University of London, School of Advanced Study
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3101412767