Benefit–Cost Analysis of Social Media Facilitated Bystander Programs

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