Quantifying Social Influence in an Online Cultural Market

We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process–the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and suggests that in this market with anonymous feedback cues, social influence serves an informational rather than normative role

Can geography lock a society in stagnation?

We extend Galor and Weil (2000) by including geographical factors in order to show that under some initial conditions, an economy may be locked in Malthusian stagnation and never take off. Specifically, we characterize the set of geographical factors for which this happens, and this way we show how the interplay of the available "land", its suitability for living, and its degree of isolation, determines whether an economy can escape stagnation

Social awareness and duopoly competition

Human actions are often guided both by individual rationality and by social norms. In this paper we explore how duopoly market competition values the variants of a product, when these variants embody at different levels the requirements derived from some social norm. In a model where preferences of consumers depend partially on the levels of compliance of the variants with the social norm, we characterize the equilibrium path along which firms choose sequentially their level of compliance and their pric

Reaching consensus on rumors

An important contribution in sociophysics is the Galam's model of rumors spreading. This model provides an explanation of rumors spreading in a population and explains some interesting social phenomena such as the diffusion of hoaxes. In this paper the model has been reformulated as a Markov process highlighting the stochastic nature of the phenomena. This formalization allows us to derive conditions for consensus to be reached and for the existence of some interesting phenomena such as the emergence of impasses. The proposed formulation allows a deeper and more comprehensive analysis of the diffusion of rumors

Can federal reserve policy deviation explain response patterns of financial markets over time?

Yes. By using real-time structure break monitoring techniques we find evidence against monotonic response pattern, specifically three response structures of US stock market to the federal monetary policy actions based on a sample from 1989-2010. We re-estimate the market response in each of the three structures and find results stronger than previously documented especially in 2001-2008. We propose a “FedGap” variable which measures the deviation of Fed policy from the “Taylor Rule” in explanation and find it to be significant with economic meaning. We conclude that market responses proportionally to the size of the FedGap and it thus serves as a new “macro-state” factor which can explain the dynamic response patterns of financial markets. We also examine the issue from the bond market, and find similar results

Trust and manipulation in social networks

We investigate the role of manipulation in a model of opinion formation where agents have opinions about some common question of interest. Agents repeatedly communicate with their neighbors in the social network, can exert some effort to manipulate the trust of others, and update their opinions taking weighted averages of neighbors’ opinions. The incentives to manipulate are given by the agents’ preferences. We show that manipulation can modify the trust structure and lead to a connected society, and thus, make the society reaching a consensus. Manipulation fosters opinion leadership, but the manipulated agent may even gain influence on the long-run opinions. In sufficiently homophilic societies, manipulation accelerates (slows down) convergence if it decreases (increases) homophily. Finally, we investigate the tension between information aggregation and spread of misinformation. We find that if the ability of the manipulating agent is weak and the agents underselling (overselling) their information gain (lose) overall influence, then manipulation reduces misinformation and agents converge jointly to more accurate opinions about some underlying true state

A general model of synchronous updating with binary opinions

URL des Documents de travail : https://centredeconomiesorbonne.univ-paris1.fr/documents-de-travail-du-ces/Documents de travail du Centre d'Economie de la Sorbonne 2019.24 - ISSN : 1955-611XWe consider a society of agents making an iterated yes/no decision on some issue, where updating is done by mutual influence under a Markovian process. Agents update their opinions at the same time, independently of each other, in an entirely mechanical manner. They can have a favourable or an unfavourable perception of their neighbours. We study the qualitative patterns of this model, which captures several notions, including conformism, anti-conformism, communitarianism and leadership. We discuss under which conditions opinions are stable. Finally, we introduce a notion of entropy that we use to extract information on the society and to predict future opinions

Modeling rates of change in individuals and populations

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 81-84).This thesis develops methodologies to measure rates of change in individual human behavior, and to capture statistical regularities in change at the population level, in three pieces: i) a model of individual rate of change as a function of search and finite resources, ii) a structural model of population level change in urban economies, and iii) a statistical test for the deviation from a null model of rank chum of items in a distribution. First, two new measures of human mobility and search behavior are defined: exploration and turnover. Exploration is the rate at which new locations are searched by an individual, and turnover is the rate at which his portfolio of visited locations changes. Contrary to expectation, exploration is open-ended for almost all individuals. A present a baseline model is developed for change (or churn) in human systems, relating rate of exploration to rate of turnover. This model recasts the neutral or random drift mechanism for population-level behavior, and distinguishes exploration due to optimization, from exploration due to a taste for variety. A relationship between the latter and income is shown. Second, there exist regular relationships in the economic structure of cities, with important similarities to ecosystems. Third, a new statistical test is developed for distinguishing random from directed churn in rank ordered systems. With a better understanding of rates of change, we can better predict where people will go, the probability of their meeting, and the expected change of a system over time. More broadly, these findings propose a new way of thinking about individual and system-level behavior: as characterized by predictable rates of innovation and change.by Coco Krumme.Ph.D

Behavioral and Psychophysiological Investigations into the Neurocognition of Social Influence

Human behavior and experience is far from independent; social norms, conveying what is typical and appropriate in a given social group, thoroughly mold what we do, think, and feel. While much is known about the motivational mechanisms of social influence based on group norms, researchers have begun to decipher its neurocognitive principles only recently. In this thesis, I provide a brief introduction into psychological investigations of social influence and recently emerging neuroscientific research in this field. Moreover, I extend previous findings and preliminary theories on the basis of eight original publications, which include one review article, one behavioral study, and six studies employing event-related brain potentials (ERPs). Upon reviewing the existent literature, I have proposed that norm-based social influence involves two core processes: (i) the differentiation of social proof and deviance in neural circuits coding behavioral outcomes, and (ii) the direct modulation of the neural representations of to-be-judged features. Moreover, my colleagues and I have tested and clarified the validity of a common behavioral measure of conformity as well as the functional significance of ERP components relevant to the investigation of outcome processing and sustained attention. Most importantly, we have built upon our synthesis of the literature and our methodological studies and provide conclusive findings that confirm and extend the proposed accounts of social influence. We demonstrate that the differentiation of norms that confirm or contradict the individual's own views—thus constituting social proof or conveying social deviance, respectively—engages both early and late processes of attentional prioritization. Episodes of social proof, as well as stimuli associated with it, take precedence over those related to deviance. This finding is replicated across different samples, tasks, and paradigms. We propose that social norms feed into basic cognitive processes, similar to the value-informed deployment of attentional resources. As a whole, my series of research corroborates the notion that social influence is based upon some of our general cognitive faculties, such as outcome valuation and reinforcement learning, and can entail modulations of even the most fundamental functions, such as perception and attention. This could explain the pervasiveness of social influence on human behavior and experience, and it speaks to the timeliness and relevance of exploring its neurocognitive foundations