Correction: Using the Dirichlet process to form clusters of people's concerns in the context of future party identification.

[This corrects the article DOI: 10.1371/journal.pone.0212944.].

Using the Dirichlet process to form clusters of people's concerns in the context of future party identification.

Connections between interindividual differences and people's behavior has been widely researched in various contexts, often by using top-down group comparisons to explain interindividual differences. In contrast, in this study, we apply a bottom-up approach in which we identify meaningful clusters in people's concerns about various areas of life (e.g., their own health, their financial situation, the environment). We apply a novel method, Dirichlet clustering, to large-scale longitudinal data from the German Socioeconomic Panel Study (SOEP) to investigate whether concerns of people living in Germany evaluated in 2010 (t0) cluster participants into robust and separable groups, and whether these groups vary regarding their party identification in 2017 (t0 + 7). Clustering results suggest a range of different groups with specific concern patterns. Some of these notably specific patterns of concerns indicate links to party identification. In particular, some patterns show an increased identification with smaller parties as the 'Bündnis 90/Die Grünen' ('Greens'), the left wing party 'Die Linke' ('The Left') or the right-wing party 'Alternative für Deutschland' ('Alternative for Germany', AfD). Considering that we identify as many as 37 clusters in total, among them at least six with clearly different party identification, it can also be concluded that the complexity of political concerns may be larger than has been assumed before.