Abstract: In the field of Data Perspectivism, perspective has emerged as an umbrella term encompassing annotators’ points of view and culturally shaped worldviews. When modeling annotators, researchers have explored a variety of potential predictors, with demographics receiving particular attention, especially following the rise of techniques such as sociodemographic prompting. In this talk, 1 will examine the field’s strong emphasis on annotators’ sociodemographic information and highlight the limitations of this approach. I will focus on challenges in annotator modeling and the complexities of addressing highly subjective linguistic phenomena, going through data collection, modeling and evaluation.

Bio: Soda Marem Lo is a PhD student at the University of Turin under the supervision of Prof. Valerio Basile. She is currently working on the Data Perspectivism framework, specifically on modeling annotators’ perspectives. Her research interests include hate speech, stereotype and irony detection, as well as the linguistic and social dimensions of these phenomena.