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Stance detection (SD) concerns automatically determining the viewpoint (i.e.,in favour of, against, or neutral) of a text's author towards a target. SD hasbeen applied to many research topics, among which the detection of stancesbehind political tweets is an important one. In this paper, we apply SD to adataset of tweets from official party accounts in the Netherlands between 2017and 2021, with a focus on stances towards traditional gender role division, adividing issue between (some) Dutch political parties. To implement and improveSD of traditional gender role division, we propose to leverage an establishedsurvey instrument from social sciences, which has been validated for thepurpose of measuring attitudes towards traditional gender role division. Basedon our experiments, we show that using such a validated survey instrument helpsto improve SD performance.

Improving Stance Detection by Leveraging Measurement Knowledge from  Social Sciences: A Case Study of Dutch Political Tweets and Traditional  Gender Role Division