Automated content analysis

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Authors: Christian Schneijderberg, Oliver Wieczorek, Isabel Steinhardt
Cited by: 0

Abstract

This chapter introduces the basic concepts underlying automated content analysis, such as natural language processing and machine learning. We will furthermore define and exemplify different types of machine learning that are important for topic modelling and sentiment analysis approaches. Afterwards, we briefly discuss how to prepare a workflow for automated content analysis and introduce literate programming to structure our coding and documentation process. We then proceed with describing data types and data structures relevant for working with APIs and text as data before closing the chapter with describing where you may find help with programming tasks online.

Fields of Study & Subjects

Computational and Text Analysis Methods Sentiment Analysis and Opinion Mining Digital Humanities and Scholarship

Publication details

Journal / source
Routledge eBooks
Pages
301–322
Publication date
15 January 2026
Language
EN
Document type
Book chapter