Rate My Professor Johan Bollen

Bollen’s research specializes in computational social science, network science, complex systems, science of science, socio-economic modeling, mental health and well-being, and collective intelligence. He has authored over 80 peer-reviewed articles, with his work cited more than 23,000 times according to Google Scholar. Key publications include “Twitter mood predicts the stock market” (Journal of Computational Science, 2011, with Huina Mao and Xiao-Jun Zeng), “Clickstream Data Yields High-Resolution Maps of Science” (PLoS ONE, 2009, with Herbert Van de Sompel et al.), “A Principal Component Analysis of 39 Scientific Impact Measures” (PLoS ONE, 2009, with Herbert Van de Sompel et al.), and “The minute-scale dynamics of online emotions reveal the effects of affect labeling” (Nature Human Behaviour, 2019, with Rui Fan et al.). His contributions have advanced usage-based metrics for research impact, social media analytics for economic prediction, and models of emotion dynamics in networks. Bollen’s projects have received funding from the National Science Foundation, Defense Advanced Research Projects Agency, Intelligence Advanced Research Projects Activity, National Institutes of Health, Economic Development Administration, NASA, and the Andrew W. Mellon Foundation, including grants for meme diffusion studies, altmetrics evaluation, and regional economic development modeling.