Developing contemporary factors of political participation

ABSTRACT

Drawing from research in communication and political science, this study identifies five factors of political participation that address both traditional and more contemporary forms of political engagement. To begin, a questionnaire was developed and tested with respondents from two nationwide surveys who answered questions about their political participation (N = 476 in Sample 1, N = 490 in Sample 2). Next, exploratory factor analysis (EFA) was conducted with responses from the first sample, and confirmatory factor analysis (CFA) was conducted with responses from the second. Both datasets yielded five distinct factors of political participation: (1) traditional political participation, (2) interpersonal political talk, (3) voting, (4) social media engagement, and (5) online information seeking. Testing convergent and discriminant validity, each factor of political participation was positively related to political efficacy and political interest. Only traditional political participation was (negatively) related to political cynicism. These results suggest that forms of political participation have become more diversified and individualized following the development of communication technologies. Therefore, each of these five factors of political participation is recommended for use in future research.

KEYWORDS:

• Political participation
• Political communication
• Media and politics
• Measurement

Notes

¹ Some prominent journals relevant to the study of political participation (e.g., Political Behavior and Electoral Studies) are not included in this study. However, we believe the items used to represent political participation in those journals are also captured by the journals targeted by this study.

² EFA is a statistical method used to identify underlying measures based on a large set of latent constructs. EFA should be conducted before using confirmatory factor analysis (CFA). CFA is accomplished with maximum likelihood estimation and is used to determine whether the data fit is confirmed or rejected based on a hypothesized measurement model (Gerbing & Hamilton, 1996).