One of the best experiences of being in the field is having mentorship chats with Data Scientists. A common scenario I find is that a Data Scientist has reached Data Scientist/Senior Data Scientist level and is looking for ways to get to the next level. I have discussed some of the contents of this post with a few folks and wanted to summarize them. To do so, I will use a simple economics framework and provide some takeaways for the reader. If you have thoughts, please feel free to engage in the comments.
With the emergence of computational social science as a field of collaboration between computer scientists and social scientists, the study of social networks and processes on these networks (social contagion) has been gaining interest. Many topics of traditional sociological interest (such as the diffusion of innovation, emergence of norms, identification of influencer) can now be studied using detailed computational models and extensive simulation.
Today, a tiny office in the sprawling edifice of the National Institutes of Health released a strategic plan. The 58-page document, complete with bullet points and clip art, spells out a direction for behavioral and social science research--including psychology, economics, and sociology--for the next four years. And while it doesn't directly shunt funding around, the plan is a bat signal for social scientists across the nation: It shows what the NIH is interested in and (likely) where grants will follow. And that could ultimately shape the direction of behavioral and social science itself. The plan comes from the Office of Behavioral and Social Science Research, an arm of the NIH that directs social science efforts within each of the agency's 27 institutes.