Differentiating language usage through topic models

•Topic models are a new way to study text and differentiate language domains.•Various techniques for topic models come with distinct validation requirements.•Unsupervised topic model identify latent patterns of language usage.•Supervised topic models identify recognized language domains.•Supervised topic models can be adapted to capture language flows across fields.

Sociologists wishing to employ topic models in their research need a helpful guide that describes the variety of topic modeling procedures, their issues, and various means of resolving them so as to convincingly answer sociological questions. We present this overview by recounting a series of our prior collaborative projects that have employed and developed various forms of topic models to understand language differentiation in academe. With each project, we encountered a variety of model-specific issues concerning the validity of topics and their suitability to our data and research questions. We developed a variety of novel visualization techniques to make sense of topic-solutions and used a variety of techniques to validate our results. In addition, we created a variety of new topic modeling techniques and procedures suitable to different kinds of data and research questions.