How text mining algorithms for crowdsourcing can help us to identify today's pressing societal issues

Crowdsourcing is increasingly applied in the area of open development with the goal to find solutions for today's pressing societal issues. To solve such wicked problems, manigold solutions need to be found and applied. In contrast to this, most recent research in crowdsourcing focuses on the few winning ideas, ignoring the sheer amount of content created by the community. In this study we address this issue by applying an automated text mining technique to analyze the ideas contributed by the crowd in an initiative tackling plastic pollution. We show that automated text mining approaches reveal numerous possibilities to make use of the so jar unused content of IT enabled collaboration projects. We further add insights into how our findings can help researchers and practitioners to accelerate the solution process for today's pressing societal issues.