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      Channels of participation: Political participant types and personality

      research-article
      1 , * , 2 , 3
      PLoS ONE
      Public Library of Science

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          Abstract

          This article employs a person-centred approach to test the relationship between personality traits and empirically defined political participant types. We argue that it is more appropriate to focus on types of participants to test the relationship between personality and political participation than on individual modes or latent dimensions of political participation. Our reasoning is that the person-centred approach allows us to learn more about how and why citizens combine different modes of participation from a tool kit of available political activities to achieve a goal as a function of their personality. We rely on data collected by the German Longitudinal Election Study 2017 (GLES, ZA6801). On the basis of a set of survey questions enquiring on political activities that people take part in, Latent Class Analysis allows us to identify three political participant types (inactives, voting specialists, and complete activists). The 10-item Big Five Inventory (BFI-10) measures respondents’ personality traits. Our findings suggest that conscientious people are more likely to affiliate with the voting specialists and extroverts with the more active participant types in Germany.

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          Most cited references43

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          Measuring personality in one minute or less: A 10-item short version of the Big Five Inventory in English and German

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            An Introduction to the Five-Factor Model and Its Applications

            The five-factor model of personality is a hierarchical organization of personality traits in terms of five basic dimensions: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience. Research using both natural language adjectives and theoretically based personality questionnaires supports the comprehensiveness of the model and its applicability across observers and cultures. This article summarizes the history of the model and its supporting evidence; discusses conceptions of the nature of the factors; and outlines an agenda for theorizing about the origins and operation of the factors. We argue that the model should prove useful both for individual assessment and for the elucidation of a number of topics of interest to personality psychologists.
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              The next Big Five Inventory (BFI-2): Developing and assessing a hierarchical model with 15 facets to enhance bandwidth, fidelity, and predictive power.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2020
                29 October 2020
                : 15
                : 10
                : e0240671
                Affiliations
                [1 ] Library, Eidgenössische Technische Hochschule, Zürich, Switzerland
                [2 ] Center for Military History and Social Sciences of the Bundeswehr, Potsdam, Germany
                [3 ] Department of Politics and International Relations, University of Aberdeen, Aberdeen, United Kingdom
                Aalborg University, DENMARK
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-8970-9686
                Article
                PONE-D-20-20548
                10.1371/journal.pone.0240671
                7595324
                33119637
                17f110be-562e-4984-9537-22ce2c4d916c
                © 2020 Johann et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 July 2020
                : 30 September 2020
                Page count
                Figures: 2, Tables: 3, Pages: 13
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Custom metadata
                Data files used are available from the GESIS database (ZA6801). See https://dbk.gesis.org/dbksearch/sdesc2.asp?no=6801&db=e¬abs=1.

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