# How we do things with words: Analyzing text as social and cultural data

## TL;DR

This paper shares experiences and best practices for computational text analysis of social and cultural data, emphasizing interdisciplinary collaboration and addressing complex social concepts.

## Contribution

It provides practical guidance and insights from diverse disciplinary backgrounds to improve computational analysis of social and cultural texts.

## Key findings

- Highlights challenges in analyzing social and cultural concepts
- Proposes best practices for interdisciplinary collaboration
- Encourages diverse methodological approaches

## Abstract

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.