This paper introduces the Causal Attitude Network (CAN) model, which conceptualizes attitudes as networks consisting of evaluative reactions and interactions between these reactions. Relevant evaluative reactions include beliefs, feelings, and behaviors toward the attitude object. Interactions between these reactions arise through direct causal influences (e.g., the belief that snakes are dangerous causes fear of snakes) and mechanisms that support evaluative consistency between related contents of evaluative reactions (e.g., people tend to align their belief that snakes are useful with their belief that snakes help maintain ecological balance). In the CAN model, the structure of attitude networks conforms to a small-world structure: evaluative reactions that are similar to each other form tight clusters, which are connected by a sparser set of ÒshortcutsÓ between them. We argue that the CAN model provides a realistic formalized measurement model of attitudes and therefore fills a crucial gap in the attitude literature. Furthermore, the CAN model provides testable predictions for the structure of attitudes and how they develop, remain stable, and change over time. Attitude strength is conceptualized in terms of the connectivity of attitude networks and we show that this provides a parsimonious account of the differences between strong and weak attitudes. We discuss the CAN model in relation to possible extensions, implication for the assessment of attitudes, and possibilities for further study. Key words: Network models, attitudes, tripartite model, connectionism, small-world consistency , recent connectionist modeling of attitudes (Monroe & Read, 2008) and recent advancements in applying network theory in psychology (e.g., Cramer, Waldorp, van der Maas, & Borsboom, 2010; for excellent discussions of the relevance of network analysis to the social sciences in general and psychology in particular see Borgatti, Mehra, Brass, & Labianca, 2009; Westaby, Pfaff, & Redding, 2014) to derive a set of requirements for a CAUSAL ATTITUDE NETWORK MODEL 6 realistic formalized measurement model of attitudes. Third, based on these requirements we develop the CAN model and discuss the proposed small-world structure of attitudes that underlies it. Fourth, we discuss the CAN modelÕs perspective on attitude formation and structure, attitude stability and change, and attitude strength. Fifth, we discuss possible extensions of the CAN model, the modelÕs implications for the assessment of attitudes, and some possible avenues for further study of the CAN model.

People are generally averse toward conflict between beliefs and/or feelings underlying their attitudes-that is, attitudinal ambivalence. This review integrates literature on attitudinal ambivalence with theories on decision making and coping strategies to gain a better understanding of when and how people deal with feelings of ambivalence. First it shows that ambivalence is experienced as being particularly unpleasant when the ambivalent attitude holder is confronted with the necessity to make a choice concerning the ambivalent attitude object; then, incongruent evaluative components of the attitude become accessible, and feelings of uncertainty about the potential outcomes arise, which may involve the anticipation of aversive emotions. Several coping strategies are employed when ambivalence is experienced as unpleasant. Emotion- and problem-focused coping strategies are discussed. The article concludes with a discussion of the MAID (model of ambivalence-induced discomfort), which aims to describe the consequences of ambivalence.

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A A Advances in Experimental SocialPsychology. Published version may differ and is available from Elsevier. ABSTRACTAs science continues to progress, attitudes towards science seem to become ever more polarized. Whereas some put their faith in science, others routinely reject and dismiss scientific evidence. The current chapter provides an integration of recent research on how people evaluate science. We organize our chapter along three research topics that are most relevant to this goal: ideology, motivation, and morality. We review the relations of political and religious ideologies to science attitudes, discuss the psychological functions and motivational underpinnings of belief in science, and describe work looking at the role of 3 morality when evaluating science and scientists. In the final part of the chapter, we apply what we know about science evaluations to the current crisis of faith in science and the open science movement. Here, we also take into account the increased accessibility and popularization of science and the (perceived) relations between science and industry. (147 words)

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In this article, we provide a brief tutorial on the estimation, analysis, and simulation on attitude networks using the programming language R. We first discuss what a network is and subsequently show how one can estimate a regularized network on typical attitude data. For this, we use open-access data on the attitudes toward Barack Obama during the 2012 American presidential election. Second, we show how one can calculate standard network measures such as community structure, centrality, and connectivity on this estimated attitude network. Third, we show how one can simulate from an estimated attitude network to derive predictions from attitude networks. By this, we highlight that network theory provides a framework for both testing and developing formalized hypotheses on attitudes and related core social psychological constructs.

This article introduces the Attitudinal Entropy (AE) framework, which builds on the Causal Attitude Network model that conceptualizes attitudes as Ising networks. The AE framework rests on three propositions. First, attitude inconsistency and instability are two related indications of attitudinal entropy, a measure of randomness derived from thermodynamics. Second, energy of attitude configurations serves as a local processing strategy to reduce the global entropy of attitude networks. Third, directing attention to and thinking about attitude objects reduces attitudinal entropy. We first discuss several determinants of attitudinal entropy reduction and show that several findings in the attitude literature, such as the mere thought effect on attitude polarization and the effects of heuristic versus systematic processing of arguments, follow from the AE framework. Second, we discuss the AE framework's implications for ambivalence and cognitive dissonance.