Social Advertising Effectiveness Using a Large-Scale Randomized Field Experiment
Study 1: Social Advertising Effectiveness
Study 2: Social Advertising Effectiveness Across Products, forthcoming in Marketing Science
We examine social advertising effectiveness and its heterogeneous effects across products, individuals, and social ties, by identifying the causal relationships among social influence, products, and network-embedded human behaviors. Social advertising places social cues (e.g., likes) in ads, utilizing the power of social influence (the effects of social cues in ads) to encourage ad engagement. We collaborate with a world-known social networking app for a large-scale randomized field experiment on its social ads. In the experiment, the presence and the number of social cues were randomly assigned among 57 million ad-user pairs (more than 37 million subjects and across 71 products in 25 product categories). Integrating the experimental evidence and the data of individuals, products, ads, and network structures, our studies also address the incentives, magnitude, contagion patterns, and viral factors (i.e., characteristics of products, behaviors, and individuals) of social influence in social advertising and product adoptions.
Emotions in Online Content Diffusion
To investigate the impact of emotions on the spread of online content, we analyzed a random sample of 387,486 online articles and their diffusion cascades, in which more than 6 million unique individuals shared the articles on a massive-scale online social network. We detected the degree of eight discrete emotions (i.e., surprise, joy, anticipation, love, anxiety, sadness, anger, and disgust) embedded in the content of each article with a newly generated domain-specific and up-to-date emotion lexicon. Our results suggest that articles with a higher degree of emotion generally reached a significantly larger number of individuals and diffused significantly more deeply, broadly, and virally but more slowly. Anxiety and love significantly increased cascade size, depth, breadth, and structural virality, whereas sadness significantly decreased these factors but accelerated article diffusion. We also find that the average age and network degree of the individuals, and especially the proportion of the weak ties involved in a cascade, significantly mediated the effects of emotions that lead to a differential diffusion process. Consistent emotions were detected between articles and the associated comments, confirming that readers well received the emotions expressed in the articles.