Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

Microblogging as an extension of science reporting.

Mass media have long provided general publics with science news. New media such as Twitter have entered this system and provide an additional platform for the dissemination of science information. Based on automated collection and analysis of >900 news articles and 70,000 tweets, this study explores the online communication of current science news. Topic modeling (latent Dirichlet allocation) was used to extract five broad themes of science reporting: space missions, the US government shutdown, cancer research, Nobel Prizes, and climate change. Using content and network analysis, Twitter was found to extend public science communication by providing additional voices and contextualizations of science issues. It serves a recommender role by linking to web resources, connecting users, and directing users' attention. This article suggests that microblogging adds a new and relevant layer to the public communication of science.