{'fraction_non_alphanumeric': 0.01691404901622368, 'fraction_numerical': 0.0017259233690024164, 'mean_word_length': 5.662068965517242, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Identifying Influential and Susceptible Individuals in Social Networks: Evidence from a Randomized Experiment

Perhaps the two most important and elusive questions at the heart of viral marketing today are when is peer-to-peer influence mobilized and who are the influentials that most effectively mobilize and propagate influence in networks and society? Answers to these questions are critical to the success of viral marketing campaigns and for understanding how behavioral contagions spread through social networks. Unfortunately, the econometric identification of peer influence and social contagion is non-trivial, making influence identification difficult in observational data. We therefore conduct a large scale randomized experiment involving millions of subjects on the popular social networking website Facebook.com to identify influence, and the characteristics of influential and susceptible individuals involved in the peer-to-peer spread of a commercial grade movie application. By activating a viral feature on the application that generates notifications of a user's activities to their social network peers and then randomizing receipt of the viral messages among peers, we create random assignment to treatment and control groups. We then estimate contagion models with random assignment of the receipt of potentially influential peer-to-peer viral messages. Our study demonstrates how randomized experiments can be used to identify influentials and susceptibles in large social networks of consumers. Introduction: We examine how firms can take advantage of detailed consumer data generated by IT-enabled products and services to identify " influential " individuals in social networks – those who are likely to effectively encourage product adoption amongst their peers – and " susceptibles " – peers that are likely to respond positively to influence. The notion that influentials exist and that such individuals are catalysts for promoting diffusion of opinions, innovations and products is a popular one The complementary notion, however, that susceptibles may be even more critical to product diffusion and the formation of widespread contagions, has been systematically understudied in the literature (Watts and Dodds 2007). As Watts and Dodds note: " In the models that we have studied, in fact, it is generally the case that most social change is driven not by influentials but by easily influenced individuals influencing other easily influenced individuals. " Despite receiving disproportionately less attention by researchers than the influentials hypothesis, the susceptibles hypothesis is well represented in a variety of theoretical threshold-based contagion models in which the adoption of an individual occurs when some number or proportion of his peers have adopted beyond his intrinsic adoption threshold. 1 Yet, empirical studies estimating the importance …