How we do things with words: Analyzing text as social and cultural data
This work addresses methodological issues for researchers in social sciences and humanities using computational text analysis, but it is incremental as it offers guidance rather than new techniques.
The authors tackle the challenges of computational text analysis for social and cultural data by providing best practices and promoting interdisciplinary collaboration, based on their diverse experiences.
In this article we describe our experiences with computational text analysis. 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 best practices for working with thick social and cultural concepts. 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 will resonate for many. And 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 that involves social and cultural concepts, and the more we are able to bridge these divides, the more fruitful we believe our work will be.