Publication: Enhancing the design of voting advice applications with BERT language model
Enhancing the design of voting advice applications with BERT language model
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Buryakov, D., Kovacs, M., Serdült, U., & Kryssanov, V. (2024). Enhancing the design of voting advice applications with BERT language model. Frontiers in Artificial Intelligence, 7, 1343214. https://doi.org/10.3389/frai.2024.1343214
Abstract
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Abstract
The relevance and importance of voting advice applications (VAAs) are demonstrated by their popularity among potential voters. On average, around 30% of voters take into account the recommendations of these applications during elections. The comparison between potential voters’ and parties’ positions is made on the basis of VAA policy statements on which users are asked to express opinions. VAA designers devote substantial time and effort to analyzing domestic and international politics to formulate policy statements and select those
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- Buryakov, Daniil
- Kovacs, Mate
- Kryssanov, Victor
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Buryakov, D., Kovacs, M., Serdült, U., & Kryssanov, V. (2024). Enhancing the design of voting advice applications with BERT language model. Frontiers in Artificial Intelligence, 7, 1343214. https://doi.org/10.3389/frai.2024.1343214
