Towards an Estonian dataset on document-level subjectivity - Karl Gustav Gailit; Kadri Muischnek; Kairit Sirts (Eesti ja Soome-ugri Keeleteaduse Ajakiri, 2025)
This article discusses a preparatory step towards developing an Estonian dataset on subjectivity, providing a brief overview of past analyses of subjectivity and the theoretical basis for creating the dataset. Subjectivity has been explored within many fields of linguistics, including pragmatics and formal semantics, as well as natural language processing where computational methods are used to create models for detecting subjectivity, often for further processing. However, many of these models could be improved, and for some it is questionable whether they classify subjectivity or something else, such as text genre. These issues are caused by the datasets these models are trained on, from the text collection method to the unnuanced labels of “objective” and “subjective”. To solve this issue, we propose a dataset of documents from various registers with annotations for subjectivity with a scalar value, where zero represents a fully objective document and one a subjective document.