Benefit–Cost Analysis of Social Media Facilitated Bystander Programs

Abstract

Bystander programs contribute to crime prevention by motivating people to intervene in violent situations. Social media allow addressing very specific target groups, and provide valuable information for program evaluation. This paper provides a conceptual framework for conducting benefit–cost analysis of bystander programs and puts a particular focus on the use of social media for program dissemination and data collection. The benefit–cost model treats publicly funded programs as investment projects and calculates the benefit–cost ratio. Program benefit arises from the damages avoided by preventing violent crime. We provide systematic instructions for estimating this benefit. The explained estimation techniques draw on social media data, machine-learning technology, randomized controlled trials and discrete choice experiments. In addition, we introduce a complementary approach with benefits calculated from the public attention generated by the program. To estimate the value of public attention, the approach uses the bid landscaping method, which originates from display advertising. The presented approaches offer the tools to implement a benefit–costs analysis in practice. The growing importance of social media for the dissemination of policy programs requires new evaluation methods. By providing two such methods, this paper contributes to evidence-based decision-making in a growing policy area.