How We Do Things With Words: Analyzing Text as Social and Cultural Data

Dong Nguyen, Maria Liakata, Simon Dedeo, Jacob Eisenstein, David Mimno, Rebekah Tromble, Jane Winters

Research output: Contribution to journalArticleAcademicpeer-review


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.
Original languageEnglish
Article number62
Number of pages14
JournalFrontiers in Artificial Intelligence
Publication statusPublished - 25 Aug 2020


  • computational text analysis
  • natural language processing
  • computational social science
  • cultural analytics
  • digital humanities


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