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The enormous potential of online peer groups in addressing social problems has attracted researchers’ attention to investigate how users support each other and benefit from participation. The extent, how users benefit in online peer groups depending on their role of contributing social support is still unexplored. To close this gap, we analyse a unique online peer group dataset in the context of unemployment from a field experiment at the German Federal Employment Agency. We build on content analysis and cluster analysis to detect user roles based on users’ contribution in the form of exchanging social support. We quantitatively compare how different users benefit from participation. Results show that users generally benefit by means of peer group effects regardless of their role. However, low-contributors get disproportionately activated and thereby benefit in dimensions where they initially lag behind other users. High-contributors disproportionately benefit in terms of acquir-ing pertinent skills.



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