ABSTRACT
The alignment of bargaining positions is crucial to a successful negotiation. Prior research has shown that similarity in language use is indicative of the conceptual alignment of interlocutors. We use latent semantic analysis to explore how the similarity of language use between negotiating parties develops over the course of a three-party negotiation. Results show that parties that reach an agreement show a gradual increase in language similarity over the course of the negotiation. Furthermore, reaching the most financially efficient outcome is dependent on similarity in language use between the parties that have the most to gain from such an outcome.
Subject(s)
Cooperative Behavior , Language , Negotiating , Humans , PsycholinguisticsABSTRACT
We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory's research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science.
Subject(s)
Morals , Reproducibility of Results , HumansABSTRACT
Both normative theories of ethics in philosophy and contemporary models of moral judgment in psychology have focused almost exclusively on the permissibility of acts, in particular whether acts should be judged on the basis of their material outcomes (consequentialist ethics) or on the basis of rules, duties, and obligations (deontological ethics). However, a longstanding third perspective on morality, virtue ethics, may offer a richer descriptive account of a wide range of lay moral judgments. Building on this ethical tradition, we offer a person-centered account of moral judgment, which focuses on individuals as the unit of analysis for moral evaluations rather than on acts. Because social perceivers are fundamentally motivated to acquire information about the moral character of others, features of an act that seem most informative of character often hold more weight than either the consequences of the act or whether a moral rule has been broken. This approach, we argue, can account for numerous empirical findings that are either not predicted by current theories of moral psychology or are simply categorized as biases or irrational quirks in the way individuals make moral judgments.
Subject(s)
Judgment , Morals , Humans , Models, PsychologicalABSTRACT
Genetic algorithms (GAs) have been used to find efficient solutions to numerous fundamental and applied problems. While GAs are a robust and flexible approach to solve complex problems, there are some situations under which they perform poorly. Here, we introduce a genetic algorithm approach that is able to solve complex tasks plagued by so-called ''golf-course''-like fitness landscapes. Our approach, which we denote variable environment genetic algorithms (VEGAs), is able to find highly efficient solutions by inducing environmental changes that require more complex solutions and thus creating an evolutionary drive. Using the density classification task, a paradigmatic computer science problem, as a case study, we show that more complex rules that preserve information about the solution to simpler tasks can adapt to more challenging environments. Interestingly, we find that conservative strategies, which have a bias toward the current state, evolve naturally as a highly efficient solution to the density classification task under noisy conditions.
Subject(s)
Algorithms , Genome , Models, Genetic , Biological Evolution , Computer Simulation , Monte Carlo MethodABSTRACT
Framing, the effect of context on cognitive processes, is a prominent topic of research in psychology and public opinion research. Research on framing has traditionally relied on controlled experiments and manually annotated document collections. In this paper we present a method that allows for quantifying the relative strengths of competing linguistic frames based on corpus analysis. This method requires little human intervention and can therefore be efficiently applied to large bodies of text. We demonstrate its effectiveness by tracking changes in the framing of terror over time and comparing the framing of abortion by Democrats and Republicans in the U.S.
Subject(s)
Public Opinion , Abortion, Induced , Algorithms , Female , Humans , Pregnancy , Research DesignABSTRACT
Social groups of interacting agents display an ability to coordinate in the absence of a central authority, a phenomenon that has been recently amplified by the widespread availability of social networking technologies. Models of opinion formation in a population of agents have proven a very useful tool to investigate these phenomena that arise independently of the heterogeneities across individuals and can be used to identify the factors that determine whether widespread consensus on an initial small majority is reached. Recently, we introduced a model in which individual agents can have conservative and partisan biases. Numerical simulations for finite populations showed that while the inclusion of conservative agents in a population enhances the population's efficiency in reaching consensus on the initial majority opinion, even a small fraction of partisans leads the population to converge on the opinion initially held by a minority. To further understand the mechanisms leading to our previous numerical results, we investigate analytically the noise driven transition from a regime in which the population reaches a majority consensus (efficient), to a regime in which the population settles in deadlock (non-efficient). We show that the mean-field solution captures what we observe in model simulations. Populations of agents with no opinion bias show a continuous transition to a deadlock regime, while populations with an opinion bias, show a discontinuous transition between efficient and partisan regimes. Furthermore, the analytical solution reveals that populations with an increasing fraction of conservative agents are more robust against noise than a population of naive agents because in the efficient regime there are relatively more conservative than naive agents holding the majority opinion. In contrast, populations with partisan agents are less robust to noise with an increasing fraction of partisans, because in the efficient regime there are relatively more naive agents than partisan agents holding the majority opinion.
Subject(s)
Consensus , Prejudice , Computer Simulation , Humans , Models, Theoretical , Public OpinionABSTRACT
Two quantitative meta-analyses examined how the presence of visual channels, vocal channels, and synchronicity influences the quality of outcomes in negotiations and group decision making. A qualitative review of the literature found that the effects of communication channels vary widely and that existing theories do not sufficiently account for these contradictory findings. To parsimoniously encompass the full range of existing data, the authors created the communication orientation model, which proposes that the impact of communication channels is shaped by communicators' orientations to cooperate or not. Two meta-analyses-conducted separately for negotiations and decision making-provide strong support for this model. Overall, the presence of communication channels (a) increased the achievement of high-quality outcomes for communicators with a neutral orientation, (b) did not affect the outcomes for communicators with a cooperative orientation, but (c) hurt communicators' outcomes with a noncooperative orientation. Tests of cross-cultural differences in each meta-analysis further supported the model: for those with a neutral orientation, the beneficial effects of communication channels were weaker within East Asian cultures (i.e., Interdependent and therefore more predisposed towards cooperation) than within Western cultures (i.e., Independent).
Subject(s)
Communication , Decision Making , Group Processes , Negotiating/psychology , Acoustic Stimulation , Humans , Interpersonal Relations , Photic Stimulation , Power, Psychological , Social Behavior , Social IdentificationABSTRACT
Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election "winner-takes-all" markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility correlations, and, usually, power-law decaying distributions of returns. However, unlike other financial markets, we find conditional diverging volatilities as the contract settlement date approaches. We propose a dynamic binary option model that captures all features of the empirical data and can potentially provide a tool with which one may extract true information events from a price time series.
ABSTRACT
Many natural and social systems display global organization and coordination without centralized control. The origin of this global coordination is a topic of great current interest. Here we investigate a density-classification task as a model system for coordination and information processing in decentralized systems. We show that sophisticated strategies, selected under idealized conditions, are not robust to environmental changes. We also demonstrate that a simple heuristic is able to successfully complete the classification task under a broad range of environmental conditions. Our findings hint at the possibility that complex networks and ecologically efficient rules coevolve over time.