Replication Data for: Cleavage Identities in Voters’ Own Words: Harnessing Open-Ended Survey Responses
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Fundamental transformations of underlying cleavage structures in advanced democracies should become evident in new collective identities. This paper uses quantitative text analysis to investigate how voters describe their in-groups and out-groups in open-ended survey responses. I look at Switzerland, a paradigmatic case of electoral realignment along a ‘second’, universalism-particularism dimension of politics opposing the far right and the new left. Keyness statistics and a semi-supervised document scaling method (latent semantic scaling) serve to identify terms associated with the poles of this divide in voters’ responses, and hence to measure universalist/particularist identities. Based on voters’ own words, the results support the idea of collective identities consolidating an emerging cleavage: voters’ identity descriptions relate t' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Affective polarization","Cleavages","Group identity","New left and far right voting","Public opinion","Quantitative text analysis","Voting behavior"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Fundamental transformations of underlying cleavage structures in advanced democracies should become evident in new collective identities. This paper uses quantitative text analysis to investigate how voters describe their in-groups and out-groups in open-ended survey responses. I look at Switzerland, a paradigmatic case of electoral realignment along a ‘second’, universalism-particularism dimension of politics opposing the far right and the new left. Keyness statistics and a semi-supervised document scaling method (latent semantic scaling) serve to identify terms associated with the poles of this divide in voters’ responses, and hence to measure universalist/particularist identities. Based on voters’ own words, the results support the idea of collective identities consolidating an emerging cleavage: voters’ identity descriptions relate t' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Fundamental transformations of underlying cleavage structures in advanced democracies should become evident in new collective identities. This paper uses quantitative text analysis to investigate how voters describe their in-groups and out-groups in open-ended survey responses. I look at Switzerland, a paradigmatic case of electoral realignment along a ‘second’, universalism-particularism dimension of politics opposing the far right and the new left. Keyness statistics and a semi-supervised document scaling method (latent semantic scaling) serve to identify terms associated with the poles of this divide in voters’ responses, and hence to measure universalist/particularist identities. Based on voters’ own words, the results support the idea of collective identities consolidating an emerging cleavage: voters’ identity descriptions relate t
Affective polarization; Cleavages; Group identity; New left and far right voting; Public opinion; Quantitative text analysis; Voting behavior