Publikation: Measuring incivility in parliamentary debates : validating a sentiment analysis procedure with calls to order in the Austrian Parliament
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Parliamentary debates sometimes see uncivil behavior by MPs and parliamentary rules of procedure provide instruments such as Calls to Order to sanction uncivil behavior. Incivility is an extreme form of negativity encountered in parliamentary debates. The varied forms of negativity found in parliamentary debates have made them a popular test field for sentiment analysis, the systematic measurement of valence in statements. This chapter describes a sentiment analysis procedure which combines context-sensitive word representations, crowdcoding of negativity in training sentences, and a neural network classifier to establish the level of negativity in debate statements. To validate the procedure we try to predict Calls to Order in the Austrian parliament. We find that we can predict Calls to Order from a statement's degree of negativity reasonably well. The procedure therefore offers great potential for a valid and reliable measurement of incivility in parliamentary debates.
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JENNY, Marcelo, Martin HASELMAYER, Daniel KAPLA, 2021. Measuring incivility in parliamentary debates : validating a sentiment analysis procedure with calls to order in the Austrian Parliament. In: WALTER, Annemarie S., ed.. Political Incivility in the Parliamentary, Electoral and Media Arena : Crossing Boundaries. London: Routledge, 2021, pp. 1-11. Routledge studies on political parties and party systems. ISBN 978-0-367-46273-4BibTex
@incollection{Jenny2021Measu-56013, year={2021}, title={Measuring incivility in parliamentary debates : validating a sentiment analysis procedure with calls to order in the Austrian Parliament}, isbn={978-0-367-46273-4}, publisher={Routledge}, address={London}, series={Routledge studies on political parties and party systems}, booktitle={Political Incivility in the Parliamentary, Electoral and Media Arena : Crossing Boundaries}, pages={1--11}, editor={Walter, Annemarie S.}, author={Jenny, Marcelo and Haselmayer, Martin and Kapla, Daniel} }
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