ENGINEERING DIGITAL SHARING PLATFORM TO CREATE SOCIAL CONTAGION: EVIDENCE FROM LARGE SCALE RANDOMIZED FIELD EXPERIMENTS

Peer-to-peer information sharing has fundamentally changed customer decision-making process. Recent developments in information technologies have enabled digital sharing platforms to influence various granular aspects of the information sharing process. Despite the growing importance of digital information sharing, little research has examined the optimal design choices for a platform seeking to maximize returns from information sharing. My dissertation seeks to fill this gap. Specifically, I study novel interventions that can be implemented by the platform at different stages of the information sharing. In collaboration with a leading for-profit platform and a non-profit platform, I conduct three large-scale field experiments to causally identify the impact of these interventions on customers’ sharing behaviors as well as the sharing outcomes. The first essay examines whether and how a firm can enhance social contagion by simply varying the message shared by customers with their friends. Using a large randomized field experiment, I find that i) adding only information about the sender’s purchase status increases the likelihood of recipients’ purchase; ii) adding only information about referral reward increases recipients’ follow-up referrals; and iii) adding information about both the sender’s purchase as well as the referral rewards increases neither the likelihood of purchase nor follow-up referrals. I then discuss the underlying mechanisms. The second essay studies whether and how a firm can design unconditional incentive to engage customers who already reveal willingness to share. I conduct a field experiment to examine the impact of incentive design on sender’s purchase as well as further referral behavior. I find evidence that incentive structure has a significant, but interestingly opposing, impact on both outcomes. The results also provide insights about senders’ motives in sharing. The third essay examines whether and how a non-profit platform can use mobile messaging to leverage recipients’ social ties to encourage blood donation. I design a large field experiment to causally identify the impact of different types of information and incentives on donor’s self-donation and group donation behavior. My results show that non-profits can stimulate group effect and increase blood donation, but only with group reward. Such group reward works by motivating a different donor population. In summary, the findings from the three studies will offer valuable insights for platforms and social enterprises on how to engineer digital platforms to create social contagion. The rich data from randomized experiments and complementary sources (archive and survey) also allows me to test the underlying mechanism at work. In this way, my dissertation provides both managerial implication and theoretical contribution to the phenomenon of peer-to-peer information sharing.

The interplay between social motivation, social experience, and developmental neural specialization for social perception

From birth, infants preferentially attend to human motion, which allows them to learn to interpret other peoples’ facial expressions and mental states. Evidence from adults shows that selectivity of the amygdala and the posterior superior temporal sulcus (pSTS) to biological motion correlates with social network size. Social motivation—one’s desire to orient to the social world, to seek and find reward in social interaction, and to maintain social relationships—may also contribute to neural specialization for biological motion and to social network characteristics. The current study aimed to determine whether neural selectivity for biological motion relates to social network characteristics, and to gain preliminary evidence as to whether social motivation plays a role in this relation. Findings suggest that neural selectivity for biological motion in the pSTS is positively related to social network size in middle childhood and that this relation is moderated by social motivation.

A VOICE OF THEIR OWN: MUSIC AND SOCIAL COHESION IN TURKISH ALEVI LIFE

This dissertation examines the role that music has played in the expression of identity and revitalization of culture of the Alevis in Turkey, since the start of their sociocultural revival movement in the late 1980s. Music is central to Alevi claims of ethnic and religious difference—singing and playing the bağlama (Turkish folk lute) constitutes an expressive practice in worship and everyday life. Based on research conducted from 2012 to 2014, I investigate and present Alevi music through the lens of discourses on the construction of identity as a social and musical process. Alevi musicians perform a revived repertoire of the ritual music and folk songs of Anatolian bards and dervish-lodge poets that developed over several centuries. Contemporary media and performance contexts have blurred former distinctions between sacred and secular, yet have provided new avenues to build community in an urban setting. I compare music performances in the worship services of urban and small-town areas, and other community events such as devotional meetings, concerts, clubs, and broadcast and social media to illustrate the ways that participation—both performing and listening—reinforces identity and solidarity. I also examine the influence of these different contexts on performers’ musical choices, and the power of music to evoke a range of responses and emotional feelings in the participants. Through my investigation I argue that the Alevi music repertoire is not only a cultural practice but also a symbol of power and collective action in their struggle for human rights and self-determination. As Alevis have faced a redefined Turkish nationalism that incorporates Sunni Muslim piety, this music has gained even greater potency in their resistance to misrecognition as a folkloric, rather than a living, tradition.

Mathematical Programming Models for Influence Maximization on Social Networks

In this dissertation, we apply mathematical programming techniques (i.e., integer programming and polyhedral combinatorics) to develop exact approaches for influence maximization on social networks. We study four combinatorial optimization problems that deal with maximizing influence at minimum cost over a social network. To our knowl- edge, all previous work to date involving influence maximization problems has focused on heuristics and approximation. We start with the following viral marketing problem that has attracted a significant amount of interest from the computer science literature. Given a social network, find a target set of customers to seed with a product. Then, a cascade will be caused by these initial adopters and other people start to adopt this product due to the influence they re- ceive from earlier adopters. The idea is to find the minimum cost that results in the entire network adopting the product. We first study a problem called the Weighted Target Set Selection (WTSS) Prob- lem. In the WTSS problem, the diffusion can take place over as many time periods as needed and a free product is given out to the individuals in the target set. Restricting the number of time periods that the diffusion takes place over to be one, we obtain a problem called the Positive Influence Dominating Set (PIDS) problem. Next, incorporating partial incentives, we consider a problem called the Least Cost Influence Problem (LCIP). The fourth problem studied is the One Time Period Least Cost Influence Problem (1TPLCIP) which is identical to the LCIP except that we restrict the number of time periods that the diffusion takes place over to be one. We apply a common research paradigm to each of these four problems. First, we work on special graphs: trees and cycles. Based on the insights we obtain from special graphs, we develop efficient methods for general graphs. On trees, first, we propose a polynomial time algorithm. More importantly, we present a tight and compact extended formulation. We also project the extended formulation onto the space of the natural vari- ables that gives the polytope on trees. Next, building upon the result for trees---we derive the polytope on cycles for the WTSS problem; as well as a polynomial time algorithm on cycles. This leads to our contribution on general graphs. For the WTSS problem and the LCIP, using the observation that the influence propagation network must be a directed acyclic graph (DAG), the strong formulation for trees can be embedded into a formulation on general graphs. We use this to design and implement a branch-and-cut approach for the WTSS problem and the LCIP. In our computational study, we are able to obtain high quality solutions for random graph instances with up to 10,000 nodes and 20,000 edges (40,000 arcs) within a reasonable amount of time.

Physiological Effects of Alcohol on Crayfish Escape Circuitry

Alcohol is one of the oldest and most widely used drugs on the planet, but the cellular mechanisms by which it affects neural function are still poorly understood. Unlike other drugs of abuse, alcohol has no specific receptor in the nervous system, but is believed to operate through GABAergic and serotonergic neurotransmitter systems. Invertebrate models offer circuits of reduced numerical complexity and involve the same cell types and neurotransmitter systems as vertebrate circuits. The well-understood neural circuits controlling crayfish escape behavior offer neurons that are modulated by GABAergic inhibition, thus making tail-flip circuitry an effective circuit model to study the cellular mechanisms of acute alcohol exposure. Crayfish are capable of two stereotyped, reflexive escape behaviors known as tail-flips that are controlled by two different pairs of giant interneurons, the lateral giants (LG) and the medial giants (MG). The LG circuit has been an established model in the neuroscience field for more than 60 years and is almost completely mapped out. In contrast, the MG is still poorly understood, but has important behavioral implications in social behavior and value-based decision making. In this dissertation, I show that both crayfish tail-flip circuitry are physiologically sensitive to relevant alcohol concentrations and that this sensitivity is observable on the single cell level. I also show that this ethyl alcohol (EtOH) sensitivity in the LG can be changed by altering the crayfish’s recent social experience and by removing descending inputs to the LG. While the MG exhibits similar physiological sensitivity, its inhibitory properties have never been studied before this research. Through the use of electrophysiological and pharmacological techniques, I show that the MG exhibits many similar inhibitory properties as the LG that appear to be the result of GABA-mediated chloride currents. Finally, I present evidence that the EtOH-induced changes in the MG are blocked through pre-treatment of the potent GABAA receptor agonist, muscimol, which underlines the role of GABA in EtOH’s effects on crayfish tail-flip circuitry. The work presented here opens the way for crayfish tail-flip circuitry to be used as an effective model for EtOH’s acute effects on aggression and value-based decision making.