Kate M. Johnson

Purity homophily in social networks.

Does sharing moral values encourage people to connect and form communities? The importance of moral homophily (love of same) has been recognized by social scientists, but the types of moral similarities that drive this phenomenon are still unknown. Using both large-scale, observational social-media analyses and behavioral lab experiments, the authors investigated which types of moral similarities influence tie formations. Analysis of a corpus of over 700,000 tweets revealed that the distance between 2 people in a social-network can be predicted based on differences in the moral purity content-but not other moral content-of their messages. The authors replicated this finding by experimentally manipulating perceived moral difference (Study 2) and similarity (Study 3) in the lab and demonstrating that purity differences play a significant role in social distancing. These results indicate that social network processes reflect moral selection, and both online and offline differences in moral purity concerns are particularly predictive of social distance. This research is an attempt to study morality indirectly using an observational big-data study complemented with 2 confirmatory behavioral experiments carried out using traditional social-psychology methodology.

Cultural differences in moral judgment and behavior, across and within societies

We review contemporary work on cultural factors affecting moral judgments and values, and those affecting moral behaviors. In both cases, we highlight examples of within-societal cultural differences in morality, to show that these can be as substantial and important as cross-societal differences. Whether between or within nations and societies, cultures vary substantially in their promotion and transmission of a multitude of moral judgments and behaviors. Cultural factors contributing to this variation include religion, social ecology (weather, crop conditions, population density, pathogen prevalence, residential mobility), and regulatory social institutions such as kinship structures and economic markets. This variability raises questions for normative theories of morality, but also holds promise for future descriptive work on moral thought and behavior.

TACIT: An open-source text analysis, crawling, and interpretation tool.

As human activity and interaction increasingly take place online, the digital residues of these activities provide a valuable window into a range of psychological and social processes. A great deal of progress has been made toward utilizing these opportunities; however, the complexity of managing and analyzing the quantities of data currently available has limited both the types of analysis used and the number of researchers able to make use of these data. Although fields such as computer science have developed a range of techniques and methods for handling these difficulties, making use of those tools has often required specialized knowledge and programming experience. The Text Analysis, Crawling, and Interpretation Tool (TACIT) is designed to bridge this gap by providing an intuitive tool and interface for making use of state-of-the-art methods in text analysis and large-scale data management. Furthermore, TACIT is implemented as an open, extensible, plugin-driven architecture, which will allow other researchers to extend and expand these capabilities as new methods become available.

The Immoral Assumption Effect Moralization Drives Negative Trait Attributions

Jumping to negative conclusions about other people’s traits is judged as morally bad by many people. Despite this, across six experiments (total N = 2,151), we find that multiple types of moral evaluations—even evaluations related to open-mindedness, tolerance, and compassion—play a causal role in these potentially pernicious trait assumptions. Our results also indicate that moralization affects negative—but not positive—trait assumptions, and that the effect of morality on negative assumptions cannot be explained merely by people’s general (nonmoral) preferences or other factors that distinguish moral and nonmoral traits, such as controllability or desirability. Together, these results suggest that one of the more destructive human tendencies—making negative assumptions about others—can be caused by the better angels of our nature.

Dictionaries and distributions: Combining expert knowledge and large scale textual data content analysis

Theory-driven text analysis has made extensive use of psychological concept dictionaries, leading to a wide range of important results. These dictionaries have generally been applied through word count methods which have proven to be both simple and effective. In this paper, we introduce Distributed Dictionary Representations (DDR), a method that applies psychological dictionaries using semantic similarity rather than word counts. This allows for the measurement of the similarity between dictionaries and spans of text ranging from complete documents to individual words. We show how DDR enables dictionary authors to place greater emphasis on construct validity without sacrificing linguistic coverage. We further demonstrate the benefits of DDR on two real-world tasks and finally conduct an extensive study of the interaction between dictionary size and task performance. These studies allow us to examine how DDR and word count methods complement one another as tools for applying concept dictionaries and where each is best applied. Finally, we provide references to tools and resources to make this method both available and accessible to a broad psychological audience.

Political psychology: Political psychology

UNLABELLED Political psychology is a dynamic field of research that offers a unique blend of approaches and methods in the social and cognitive sciences. Political psychologists explore the interactions between macrolevel political structures and microlevel factors such as decision-making processes, motivations, and perceptions. In this article, we provide a broad overview of the field, beginning with a brief history of political psychology research and a summary of the primary methodological approaches in the field. We then give a more detailed account of research on ideology and social justice, two topics experiencing a resurgence of interest in current political psychology. Finally, we cover research on political persuasion and voting behavior. By summarizing these major areas of political psychology research, we hope to highlight the wide variety of theoretical and methodological approaches of cognitive scientists working at the intersection of psychology and political science. WIREs Cogn Sci 2014, 5:373-385. doi: 10.1002/wcs.1293 For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST The authors have declared no conflicts of interest for this article.

Conversation level syntax similarity metric

The syntax and semantics of human language can illuminate many individual psychological differences and important dimensions of social interaction. Accordingly, psychological and psycholinguistic research has begun incorporating sophisticated representations of semantic content to better understand the connection between word choice and psychological processes. In this work we introduce ConversAtion level Syntax SImilarity Metric (CASSIM), a novel method for calculating conversation-level syntax similarity. CASSIM estimates the syntax similarity between conversations by automatically generating syntactical representations of the sentences in conversation, estimating the structural differences between them, and calculating an optimized estimate of the conversation-level syntax similarity. After introducing and explaining this method, we report results from two method validation experiments (Study 1) and conduct a series of analyses with CASSIM to investigate syntax accommodation in social media discourse (Study 2). We run the same experiments using two well-known existing syntactic metrics, LSM and Coh-Metrix, and compare their results to CASSIM. Overall, our results indicate that CASSIM is able to reliably measure syntax similarity and to provide robust evidence of syntax accommodation within social media discourse.