Eliot R. Smith, Ph.D. - US grants

Existing theories of social judgement involve information integration processes or the use of general, schematic knowledge. As an alternative, this proposal outlines a new exemplar-based model of social judgement that emphasizes the important role of the perceiver's specific past experiences. The model rests on three postulates: (1) Exemplar representations are stored in memory as they are interpreted by the perceiver and are retrieved to make social judgements, in a type of implicit memory. (2) A target stimulus serves as a cue for the retrieval of the most similar exemplars from memory. Similarity is not a fixed property of a set of stimuli, but depends on how perceivers process them, and specifically on how much attention perceivers accord to the various stimulus dimensions (Medin & Schaffer 1978). (3) A range of intrinsically social and motivational factors, including perceiver individual differences, past experiences, self-schemas, the social context, and ingroup-outgroup dynamics, have their effects on social judgement by affecting perceivers' attention to dimensions. These three postulates constitute a framework that theoretically unifies and integrates a range of known social influences on judgement by showing that they all operate through a common exemplar-based judgement mechanism. The framework also suggests testable new predictions. Eleven experiments as well as computer stimulations are proposed to further develop and test this theory. The long-term objective of this research is to increase our understanding of the social and cognitive processes involved in social judgement-- particularly effects of the perceiver's past experience and social knowledge (including stereotypes of social groups) on perceptions of and reactions to target persons and groups. Stereotypes and person perception processes are crucially important in many areas including psychiatric diagnosis, close personal relationships, and intergroup relations.

DESCRIPTION (Applicant's Abstract): This is an application for continued support of an ongoing program of research on the mental representations and processes that underlie significant phenomena in social psychology, particularly social judgement and inference, person perception, and stereotyping. These topics relate to mental health in several ways. For example, stereotypes contribute to concrete social conditions (such as prejudice and discrimination) that affect many people's mental health, and negative stereotypes also affect people's reactions to the mentally ill. The proposal's major objective is to continue developing and testing a new class of connectionist theoretical models, which are based on the properties of multiple interconnected processing units rather than symbolic representations and rules, within social psychology. Predictions from such models, generated in precise form by computer simulations. Will be compared with results from existing studies and three empirical studies will be conducted under this proposal, on the topics of accessibility of mental representations, stereotype change, and connectionist models of attitudes, motives, and social influence and interaction. The broader goals of this research are (a) to contribute to the further development of connectionist models by relating them to core theories and findings of social psychology; (b) to work toward incorporating social psychology within the increasing integration of various areas of psychology (particularly cognitive, developmental, and behavioral neuroscience) that has been driven by the increased use of connectionist models in many areas; and (c) to use connectionist models to shed new light on key aspects of social judgement and behavior, especially person perception, stereotyping, and prejudice.

This is a request for an Independent Scientist Award (K02). The applicant's immediate goals are to continue developing his knowledge and skills in connectionist (or parallel distributed processing) models in general, and applying those models within social psychology. This work fits within his long-term career goal of building integrative theory of mental representations and processes within social psychology. The career development plan involv3es building knowledge and skills related to connectionist models through relevant books, journals, and conferences; continuing to work with computer simulations of connectionist models applied to social psychological topics; and improving the accessibility of connectionist modeling for social psychologists in general. This work will take place at Purdue University, an extremely supportive training environment that offers access to numerous researchers with relevant expertise. The research plan is to continue developing and testing connectionist models with social psychology. The models' predictions, made precise and explicit by computer simulations, will be compared against results from existing studies in the field. When the models generate new predictions that have not yet been empirically tested, new laboratory studies of such predictions will be conducted; there are already several examples of new predictions that have not been confirmed by empirical test. Past and current research has related properties of connectionist models to memory for social schemas and exemplars, accessibility, heuristic- systematic and other related dual process models, stereotype learning and change, language and autobiographical memory, and flexibility of the self-concept and other knowledge representations. Planned work will continue in these areas and others including representation of attitudes, motivation and the affect-cognition interface, social interaction, and social influence. The overall goal of both training and research is to use connectionist models to generate new insights into core social psychological phenomena, incorporating social psychology within the new wave of theoretical integration that appears to be building across all of psychology through the common theoretical language of connectionist models.

When people draw on information from their individual experiences and local surroundings and use it to make a decision or judgment on a particular issue, some individuals may obtain information permitting them to make a correct decision. In contrast, others may obtain biased or inadequate samples of information. In situations like this, pooling informational resources among a number of people may help the group as a whole arrive at a better decision. This proposal outlines two projects examining how individuals can draw upon information that flows through social networks of friends and acquaintances, and use it in making their individual decisions. The process is dynamic, for as each individual draws on others' input to make decisions, his or her decisions in turn provide additional information to others in the network. Each project considers the relationships of variables at several levels, from individual agents' decision strategies (e.g., how much weight to give socially provided versus individually obtained information), to inter-agent interactions in which agents exchange information, to the overall structures of social networks. The first project considers multiple agents who are sharing information and influencing each others' choices on a particular decision (such as the choice of consumer products, or the preference for a particular social policy). The second project considers multiple agents who are assessing each other as potential partners or mates, and examines how these decisions are influenced by the spread of information about the agents themselves through the social network. Both projects will use multi-agent simulation techniques and empirical studies with human participants. The projects will have several types of broader impacts. They will increase interdisciplinary interchange, by applying novel multi-agent simulation techniques in combination with social psychological theories and empirical findings, to deepen our understanding of the role of information flow through social networks in the decision-making process. The first project may help develop ways for people to more efficiently draw on the information and experiences of others as they make their own individual decisions (e.g., purchasing consumer products) and thereby improve the outcomes of those decisions. Finally, the second project may ultimately help enhance understanding of how people select others as partners or mates, and perhaps improve the quality of those decisions - with a potential impact on the high divorce rate in society and on the multiple social problems to which it contributes.

Prejudice and discrimination by members of one group against members of another group is ubiquitous. This collaborative research project aims to better understand the conditions under which emotions felt toward other groups can exacerbate or reduce prejudice and discrimination. Research has already shown that antipathy and intolerance between groups is often driven by specific emotions (such as anger and resentment, fear and anxiety, sympathy, or guilt) that are aroused when people encounter members of other groups. The two sets of studies in this proposal focus on two important antecedents of specific emotions directed at other groups. In the first set of studies changes in people's perceived group membership is examined. The impact of these changes in categorization on emotions is assessed as well as the potential effects of an individual's emotional state on the categorization process itself. The second set of studies examines personal contact with an individual member of another group as a way of understanding the specific emotions that contribute to a positive outcome, and how these emotions translate into overt behavior in encounters between groups. Taken together, findings from this research will show how preconditions influence emotions which then translate into prejudice and behavior, and how this sequence might be altered or short-circuited. By showing when and how emotions toward other groups can exacerbate or reduce prejudice and discrimination, these research results may illuminate ways of reducing these important social problems.

The research supported by this grant innovates beyond traditional approaches to studying impression formation. Impression formation, which has been a core topic in social psychology for a long time, has generally been treated as a purely cognitive process within one perceiver. This research instead examines impressions in the context of the social network, as emerging when many people interact and share information with others. People's impressions of others are fundamental tools for social life. They influence whether we trust someone's opinion, or choose to befriend, date, or cooperate with someone. While existing research has clarified many of the cognitive processes involved in forming impressions, other important aspects remain unexamined, especially the ways perceivers incorporate information about another person passed along by others rather than relying solely on firsthand observations. A fuller picture of impression formation must involve not only cognitive processes within the individual perceiver, but also dyadic interaction processes through which perceivers actively elicit information from others, and processes of information flow in social networks.

The research proposed uses computational modeling and experimental approaches to address four key questions: (1) How do impressions differ when perceivers can actively choose what and how much information they receive about a person, rather than being limited to a fixed, pre-specified body of information (as in most existing research)? (2) Are perceivers aware of others' general reputations, and how do those reputations affect the perceiver's own impression? (3) Are perceivers aware of potential biases in socially transmitted information and can they correct for such bias? (4) How does asymmetric familiarity influence interpersonal interaction, when person A knows a lot about B (learned from third parties) but B does not know A at all? The research findings resulting from this will have implications for prejudice and stereotyping, which are also constructed and spread through social networks, and will address questions that are important to people's daily lives. In addition to the scientific advances that will result from this work, the project also aims to promote teaching, training, and learning among undergraduate and graduate students.

This is a small RAPID award to provide support for a project involving the analysis of the emotional content of large-scale Twitter data to shed light on important and enduring theoretical questions in Social Psychology. The investigators have expertise in Social Informatics and Social Psychology, and together they will collect and analyze a large-scale collection of tweets (short messages broadcast using the Twitter social networking service) that reference the Haiti earthquake disaster. The emotional content of these tweets will be tracked over time in an automated fashion using an expanded version of the Profile of Mood States test previously developed by one of the PIs. The social networks connecting Twitter users will be traced from users' "Friend of" and "Follower" data which will enable the researchers to examine the bi-directional influence of social factors with emotional responses and prosocial behavior. This analysis of Twitter data (both tweet content and social networking data of Follower and Friends networks) will permit an analysis of the impact of emotions on donating or other forms of prosocial behavior, as well as the effect of donating on subsequent emotional states. Using Twitter data to address what represents longstanding theoretical issues in Social Psychology allows the researchers to avoid many of the limitations of laboratory-based studies that include generally short time duration, practical and ethical limitations on the use of high impact manipulations, and often a reliance on college undergraduates as participants.

The broader impacts of this work are two-fold. First, the proposed program of research will promote teaching, training, and learning, by training and mentoring undergraduate research assistants and graduate students. Second, the proposed research will address questions that can be applied more broadly, to understand why and how people donate or perform other prosocial behaviors, and to encourage them to do so more frequently. Knowing what emotional states tend to lead to donation, and how people respond to information about their friends or acquaintances donations will allow charitable organizations to construct more effective appeals.

Robots are projected to become ubiquitous in homes, hospitals, schools, and other everyday spaces, where they will have to interact not with experts but rather with ordinary people - adults, the elderly, and children, from different cultural backgrounds. But untrained users may have negative beliefs, emotions, and attitudes about robots, due to lack of familiarity, which present potential challenges to their acceptance. Furthermore, multiple people will interact with multiple robots. Interaction between human and robot groups may be especially problematic, because intergroup interactions among humans are generally more negative, uncooperative, and aggressive than interactions between individuals, and human reactions to technological artifacts often resemble their reactions to other humans. In this project the PI will draw upon research from social psychology that has examined stereotyping, prejudice, and intergroup conflict, and will apply established and validated theories and methods to develop: (a) measures that can be used to understand the extent, nature, and bases of people's negative reactions to robots; (b) theoretical models of the causes and consequences of these negative reactions; and (c) interventions that demonstrably reduce negative beliefs, attitudes, and behavior in intergroup human-robot interaction (HRI). Project outcomes will suggest ways to reduce or eliminate crucial barriers to future robotics applications that are due to people's beliefs, attitudes, and emotions.

Nine studies will be conducted over three years. In Year 1, online and in-person measures will be administered to understand participant attitudes toward robots, and investigate fundamental factors that contribute to negative reactions. In Year 2, group contact, perspective taking, and long term exposure will be explored as ways to reduce prejudice toward robots. In Year 3, two more approaches to prejudice reduction in HRI will be tested: recategorization and norm-based intervention. A final study will evaluate the interaction and design strategies found to be most successful in fostering positive intergroup HRI by implementing them in robots interacting with people in a naturalistic setting. The studies will involve participants of different ages, socio-economic status, and cultural background (including four studies in Japan). Because HRI has mostly focused to date on one-on-one interactions between people and robots, this application of psychological theory to HRI in groups has vast transformative potential.