This OER is intended as a way for you to get to know text analytics at an efficient level. While there is much more to know and learn about text analytics than could be covered in a single OER, we aim to provide you with a starting point. After completing this OER, we intend for you to be familiar with different perspectives on how text analysis is approached within linguistics and data science. 

You will also learn some common ways of performing text analytics for different purposes and a little about which methodological considerations are relevant for each of the discussed methods. We hope this familiarity will make it possible for you to explore the methods further and proceed towards whatever your personal goals of utilizing text analytics might be.

You will also gain a more profound familiarity with the tool we have chosen for the applications in the OER: KNIME. KNIME is a low-code tool used for many different digital analysis tasks, and we feel that it provides a good starting point for text analytics. This is because KNIME makes the processes behind the methods you are about to learn very explicit and offers many ways of expanding your practical repertoire further after completing the OER.