Description
Taking stance towards any topic, event or idea is a common phenomenon on Twitter and social media in general. Twitter users express their opinions about different matters and assess other people’s opinions in various discursive ways.The identification and analysis of the linguistic ways that people use to take different stances leads to a better understanding of the language and user behaviour on Twitter.
Stance is a multidimensional concept involving a broad range of related notions such as modality, evaluation and sentiment. In this talk, I will present my recent study with my colleagues Carita Paradis and Eleni Seitanidi on Twitter data stance annotation and evaluation. In this study, we annotated data from Twitter using six notional stance categories ––contrariety, hypotheticality, necessity, prediction, source of knowledge and uncertainty–– following a comprehensive annotation protocol including intercoder reliability measurements. The relatively low agreement between annotators highlighted the challenges that the task entailed, which made us question the inter-annotator agreement score as a reliable measurement of annotation quality of notional categories.
In this talk, the nature of the data, the difficulty of the stance annotation task and the type of stance categories will be described, and potential solutions will be discussed.
| Period | 2023 May 30 |
|---|---|
| Event title | Research Specialization Seminar (Colloquium) of the MA Programme, School of German Language and Literature of the Aristotle University of Thessaloniki |
| Event type | Seminar |
| Location | Thessaloniki, GreeceShow on map |