How we do things with words: Analyzing text as social and cultural data
arXiv:1907.01468 · doi:10.3389/frai.2020.00062
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.
References in corpus (11)
- Model Cards for Model Reporting
- Unmasking Clever Hans Predictors and Assessing What Machines Really Learn
- Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads
- Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions
- Characterizing the Google Books corpus: Strong limits to inferences of socio-cultural and linguistic evolution
- Empath: Understanding Topic Signals in Large-Scale Text
- Gender identity and lexical variation in social media
- Diffusion of Lexical Change in Social Media
- Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions
- Exploration and Exploitation of Victorian Science in Darwin's Reading Notebooks
- Predicting Relevance based on Assessor Disagreement: Analysis and Practical Applications for Search Evaluation