scholarly journals Enhancing and accelerating social science via automation: Challenges and opportunities

2019 ◽  
Author(s):  
Tal Yarkoni ◽  
Dean Eckles ◽  
James Heathers ◽  
Margaret Levenstein ◽  
Paul Smaldino ◽  
...  
Keyword(s):  
Social Science ◽  
Social Science Research ◽  
Cost Effective ◽  
Science Research ◽  
Data Access ◽  
The Social ◽  
Challenges And Opportunities ◽  
Core Areas ◽  
Near Term ◽  
Machine Readable

Automation plays an increasingly important role in science, but the social sciences have been comparatively slow to take advantage of emerging technologies and methods. In this review, we argue that greater investment in automation would be one of the most effective and cost-effective ways to boost the reliability, validity, and utility of social science research. We identify five core areas ripe for potentially transformative investment, including (1) machine-readable standards, (2) data access platforms, (3) search and discoverability, (4) claim validation, and (5) insight generation. In each case, we review limitations associated with current practices, identify concrete opportunities for improvement via automation, and discuss near-term barriers to progress. We conclude with a discussion of practical and ethical considerations researchers will need to keep in mind when working to enhance and accelerate social science progress via automation.

scholarly journals A New Model for Industry–Academic Partnerships

2019 ◽  
Vol 53 (4) ◽  
pp. 703-709 ◽  
Author(s):  
Gary King ◽  
Nathaniel Persily
Keyword(s):  
Social Science ◽  
Social Science Research ◽  
Science Research ◽  
Data Access ◽  
Private Companies ◽  
Consumer Privacy ◽  
The Social ◽  
Charitable Foundations ◽  
Academic Partnerships ◽  
The Impact

ABSTRACTThe mission of the social sciences is to understand and ameliorate society’s greatest challenges. The data held by private companies, collected for different purposes, hold vast potential to further this mission. Yet, because of consumer privacy, trade secrets, proprietary content, and political sensitivities, these datasets are often inaccessible to scholars. We propose a novel organizational model to address these problems. We also report on the first partnership under this model, to study the incendiary issues surrounding the impact of social media on elections and democracy: Facebook provides (privacy-preserving) data access; eight ideologically and substantively diverse charitable foundations provide initial funding; an organization of academics we created, Social Science One, leads the project; and the Institute for Quantitative Social Science at Harvard and the Social Science Research Council provide logistical help.

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