Morteza Dehghani

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.

Analyzing Political Rhetoric in Conservative and Liberal Weblogs Related to the Construction of the “Ground Zero Mosque”

ABSTRACT We use different text-processing algorithms to gain insight into the political rhetoric used in conservative and liberal weblogs. We specifically focus on the online debate regarding the issue of the “Ground Zero Mosque,” which has been one of the most controversial political issues in U.S. politics in the last several years. Overall, our results show that there are significant differences in the use of various linguistic features related to sentiments of collective identity, moral concerns, and emotional dynamics between liberals and conservatives, thus highlighting the differences between the ideological and moral frameworks of these two groups.

Measuring Moral Rhetoric in Text

In this paper we present a computational text analysis technique for measuring the moral loading of concepts as they are used in a corpus. This method is especially useful for the study of online corpora as it allows for the rapid analysis of moral rhetoric in texts such as blogs and tweets as events unfold. We use latent semantic analysis to compute the semantic similarity between concepts and moral keywords taken from the “Moral foundation Dictionary”. This measure of semantic similarity represents the loading of these concepts on the five moral dimensions identified by moral foundation theory. We demonstrate the efficacy of this method using three different concepts and corpora.

Processing Narratives Concerning Protected Values: A Cross-Cultural Investigation of Neural Correlates

Abstract Narratives are an important component of culture and play a central role in transmitting social values. Little is known, however, about how the brain of a listener/reader processes narratives. A receivers response to narration is influenced by the narrators framing and appeal to values. Narratives that appeal to “protected values,” including core personal, national, or religious values, may be particularly effective at influencing receivers. Protected values resist compromise and are tied with identity, affective value, moral decision‐making, and other aspects of social cognition. Here, we investigated the neural mechanisms underlying reactions to protected values in narratives. During fMRI scanning, we presented 78 American, Chinese, and Iranian participants with real‐life stories distilled from a corpus of over 20 million weblogs. Reading these stories engaged the posterior medial, medial prefrontal, and temporo‐parietal cortices. When participants believed that the protagonist was appealing to a protected value, signal in these regions was increased compared with when no protected value was perceived, possibly reflecting the intensive and iterative search required to process this material. The effect strength also varied across groups, potentially reflecting cultural differences in the degree of concern for protected values.

Combining Distributed Vector Representations for Words

Recent interest in distributed vector representations for words has resulted in an increased diversity of approaches, each with strengths and weaknesses. We demonstrate how diverse vector representations may be inexpensively composed into hybrid representations, effectively leveraging strengths of individual components, as evidenced by substantial improvements on a standard word analogy task. We further compare these results over different sizes of training sets and find these advantages are more pronounced when training data is limited. Finally, we explore the relative impacts of the differences in the learning methods themselves and the size of the contexts they access.

Resisting temptation for the good of the group: Binding moral values and the moralization of self-control.

When do people see self-control as a moral issue? We hypothesize that the group-focused “binding” moral values of Loyalty/betrayal, Authority/subversion, and Purity/degradation play a particularly important role in this moralization process. Nine studies provide support for this prediction. First, moralization of self-control goals (e.g., losing weight, saving money) is more strongly associated with endorsing binding moral values than with endorsing individualizing moral values (Care/harm, Fairness/cheating). Second, binding moral values mediate the effect of other group-focused predictors of self-control moralization, including conservatism, religiosity, and collectivism. Third, guiding participants to consider morality as centrally about binding moral values increases moralization of self-control more than guiding participants to consider morality as centrally about individualizing moral values. Fourth, we replicate our core finding that moralization of self-control is associated with binding moral values across studies differing in measures and design—whether we measure the relationship between moral and self-control language across time, the perceived moral relevance of self-control behaviors, or the moral condemnation of self-control failures. Taken together, our findings suggest that self-control moralization is primarily group-oriented and is sensitive to group-oriented cues.

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.

Linguistic positivity in historical texts reflects dynamic environmental and psychological factors.

Significance For nearly 50 y social scientists have observed that across cultures and languages people use more positive words than negative words, a phenomenon referred to as “linguistic positivity bias” (LPB). Although scientists have proposed multiple explanations for this phenomenon—explanations that hinge on mechanisms ranging from cognitive biases to environmental factors—no consensus on the origins of LPB has been reached. In this research, we derive and test, via natural language processing and data aggregation, divergent predictions from dominant explanations of LPB by examining it across time. We find that LPB varies across time and therefore cannot be explained simply as the product of cognitive biases and, further, that these variations correspond to fluctuations in objective circumstances and subjective mood. People use more positive words than negative words. Referred to as “linguistic positivity bias” (LPB), this effect has been found across cultures and languages, prompting the conclusion that it is a panhuman tendency. However, although multiple competing explanations of LPB have been proposed, there is still no consensus on what mechanism(s) generate LPB or even on whether it is driven primarily by universal cognitive features or by environmental factors. In this work we propose that LPB has remained unresolved because previous research has neglected an essential dimension of language: time. In four studies conducted with two independent, time-stamped text corpora (Google books Ngrams and the New York Times), we found that LPB in American English has decreased during the last two centuries. We also observed dynamic fluctuations in LPB that were predicted by changes in objective environment, i.e., war and economic hardships, and by changes in national subjective happiness. In addition to providing evidence that LPB is a dynamic phenomenon, these results suggest that cognitive mechanisms alone cannot account for the observed dynamic fluctuations in LPB. At the least, LPB likely arises from multiple interacting mechanisms involving subjective, objective, and societal factors. In addition to having theoretical significance, our results demonstrate the value of newly available data sources in addressing long-standing scientific questions.

A Data-Driven Approach for Classification of Subjectivity in Personal Narratives.

Personal narratives typically involve a narrator who participates in a sequence of events in the past. The narrator is therefore present at two narrative levels: (1) the extradiegetic level, where the act of narration takes place, with the narrator addressing an audience directly; and (2) the diegetic level, where the events in the story take place, with the narrator as a participant (usually the protagonist). Although story understanding is commonly associated with semantics of the diegetic level (i.e., understanding the events that take place within the story), personal narratives may also contain important information at the extradiegetic level that frames the narrated events and is crucial for capturing the narrator’s intent. We present a data-driven modeling approach that learns to identify subjective passages that express mental and emotional states of the narrator, placing them at either the diegetic or extradiegetic level. We describe an experiment where we used narratives from personal weblog posts to measure the effectiveness of our approach across various topics in this narrative genre.

The Role of Self-Sacrifice in Moral Dilemmas

Centuries’ worth of cultural stories suggest that self-sacrifice may be a cornerstone of our moral concepts, yet this notion is largely absent from recent theories in moral psychology. For instance, in the footbridge version of the well-known trolley car problem the only way to save five people from a runaway trolley is to push a single man on the tracks. It is explicitly specified that the bystander cannot sacrifice himself because his weight is insufficient to stop the trolley. But imagine if this were not the case. Would people rather sacrifice themselves than push another? In Study 1, we find that people approve of self-sacrifice more than directly harming another person to achieve the same outcome. In Studies 2 and 3, we demonstrate that the effect is not broadly about sensitivity to self-cost, instead there is something unique about sacrificing the self. Important theoretical implications about agent-relativity and the role of causality in moral judgments are discussed.