Opinion dynamics with varying susceptibility to persuasion

A long line of work in social psychology has studied variations in people's susceptibility to persuasion -- the extent to which they are willing to modify their opinions on a topic. This body of literature suggests an interesting perspective on theoretical models of opinion formation by interacting parties in a network: in addition to considering interventions that directly modify people's intrinsic opinions, it is also natural to consider interventions that modify people's susceptibility to persuasion. In this work, we adopt a popular model for social opinion dynamics, and we formalize the opinion maximization and minimization problems where interventions happen at the level of susceptibility. We show that modeling interventions at the level of susceptibility lead to an interesting family of new questions in network opinion dynamics. We find that the questions are quite different depending on whether there is an overall budget constraining the number of agents we can target or not. We give a polynomial-time algorithm for finding the optimal target-set to optimize the sum of opinions when there are no budget constraints on the size of the target-set. We show that this problem is NP-hard when there is a budget, and that the objective function is neither submodular nor supermodular. Finally, we propose a heuristic for the budgeted opinion optimization and show its efficacy at finding target-sets that optimize the sum of opinions compared on real world networks, including a Twitter network with real opinion estimates

Commitments to help by children: Effects on subsequent prosocial self-attributions

Children of both sexes and at several ages were or were not induced to make a commitment to help hospitalized children by sorting papers

Limitations of Global Norms on Global Conservation: Using Provincial Norms to Motivate Pro-Environmental Behavior

Two field experiments examined the effectiveness of signs requesting hotel guests' participation in an environmental conservation program. Appeals employing descriptive norms (e.g., "the majority of guests reuse their towels") proved superior to a widely used traditional appeal that focused solely on environmental protection. Moreover, normative appeals were most effective when describing group behavior that occurred in the setting that most closely matched consumers' immediate situational circumstances (e.g., "the majority of guests in this room reuse their towels"), which we refer to as provincial norms. Additional experiments conceptually replicate this finding and help elucidate mechanisms driving the effect of provincial norms

The Influence of Early Respondents: Information Cascade Effects in Online Event Scheduling

Sequential group decision-making processes, such as online event scheduling, can be subject to social influence if the decisions involve individuals’ subjective preferences and values. Indeed, prior work has shown that scheduling polls that allow respondents to see others’ answers are more likely to succeed than polls that hide other responses, suggesting the impact of social influence and coordination. In this paper, we investigate whether this difference is due to information cascade effects in which later respondents adopt the decisions of earlier respondents. Analyzing more than 1.3 million Doodle polls, we found evidence that cascading effects take place during event scheduling, and in particular, that early respondents have a larger influence on the outcome of a poll than people who come late. Drawing on simulations of an event scheduling model, we compare possible interventions to mitigate this bias and show that we can optimize the success of polls by hiding the responses of a small percentage of low availability respondents.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134703/1/Romero et al 2017 (WSDM).pd

Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions

In online communities, antisocial behavior such as trolling disrupts constructive discussion. While prior work suggests that trolling behavior is confined to a vocal and antisocial minority, we demonstrate that ordinary people can engage in such behavior as well. We propose two primary trigger mechanisms: the individual's mood, and the surrounding context of a discussion (e.g., exposure to prior trolling behavior). Through an experiment simulating an online discussion, we find that both negative mood and seeing troll posts by others significantly increases the probability of a user trolling, and together double this probability. To support and extend these results, we study how these same mechanisms play out in the wild via a data-driven, longitudinal analysis of a large online news discussion community. This analysis reveals temporal mood effects, and explores long range patterns of repeated exposure to trolling. A predictive model of trolling behavior shows that mood and discussion context together can explain trolling behavior better than an individual's history of trolling. These results combine to suggest that ordinary people can, under the right circumstances, behave like trolls.Comment: Best Paper Award at CSCW 201

(De)marketing to Manage Consumer Quality Inferences

Savvy consumers attribute a product’s market performance to its intrinsic quality as well as the seller’s marketing push. The authors study how sellers should optimize their marketing decisions in response. They find that a seller can benefit from “demarketing” its product, meaning visibly toning down its marketing efforts. Demarketing lowers expected sales ex ante but improves product quality image ex post, as consumers attribute good sales to superior quality and lackluster sales to insufficient marketing. The authors derive conditions under which demarketing can be a recommendable business strategy. A series of experiments confirm these prediction

Work-Unit Absenteeism: Effects of Satisfaction, Commitment, Labor Market Conditions, and Time

Prior research is limited in explaining absenteeism at the unit level and over time. We developed and tested a model of unit-level absenteeism using five waves of data collected over six years from 115 work units in a large state agency. Unit-level job satisfaction, organizational commitment, and local unemployment were modeled as time-varying predictors of absenteeism. Shared satisfaction and commitment interacted in predicting absenteeism but were not related to the rate of change in absenteeism over time. Unit-level satisfaction and commitment were more strongly related to absenteeism when units were located in areas with plentiful job alternatives