Методы классификации текстовых данных: можно ли потенциал количественного анализа использовать в качественном исследовании?
Text mining has developed rapidly in recent years. In this article, we compare classification methods that are suitable for solving problems of predicting item nonresponse. The author builds reasoning about how the analysis of textual data can be implemented in a wider research field based on this material. The author considers a number of metrics adapted for textual analysis in the social sciences: accuracy, precision, recall, F1-score, and gives examples that can help a sociologist figure out which of them is worth paying attention depending on the task at hand (classify text data with equal accuracy, or more fully describe one of the classes of interest). The article proposes an analysis of results obtained by analyzing texts based on the materials of the European Social Survey (ESS).