Enhancing Crowd Creativity as Innovation via Teamwork: Dataset

These data files correspond to the results produced in the following paper currently accepted for publication. Pradeep K. Murukannaiah, Nirav Ajmeri, and Munindar P. Singh. 2022. Enhancing Creativity as Innovation via Asynchronous Crowdwork. In Proceedings of the 14th ACM Web Science Conference. Pages 1--9. To Appear. ---------- Data files ---------- * all_scenarios.csv: 1,823 scenarios produced by MTurk workers * rated_scenarios.csv: 639 scenarios rated for creativity by three authors (700 scenarios were randomly selected for rating. 61 scenarios of these 700 scenarios were unclear or irrelevant and thus were discarded) * creativity.csv: data for RQ1 (Creativity) * personality-creativty.csv and team-composition-creativity.csv: data for RQ2 (Personality) * efficiency.csv: data for RQ3 (Efficiency) * emotions.csv: data for RQ4 (Emotions)