This article presents a computational framework for understanding how media information about environmental problems influences cognition, emotion, and behaviour. The theoretical assumptions are formally specified and implemented in the computer model ITERA (Intuitive Thinking in Environmental Risk Appraisal) using a constraint satisfaction network. The model

Levin, Schneider and Gaeth (1998) identified three distinct types of framing effects in the literature: attribute-framing effects, goal-framing effects, risky choice-framing effects. While most previous framing studies used between-subjects manipulations of frame, the present study used two sessions, spaced one week apart, to give each of 102 participants both framing conditions and all three types of framing. Using the difference between the score for the positive framing condition and the negative framing condition as the unit of analysis for each type of framing effect, the following were found: 1) reliable framing effects for attribute framing and risky choice framing, but not for goal framing; 2) distributions of individual framing effects showing that the aggregate-level effects were representative of individuals even though some individuals showed no framing effects; 3) no significant interdependencies between the three categories of framing effects; 4) individual differences in reaction to the task scenarios related to various of the "Big Five " personality traits as well as the Faith in Intuition scale. The use of within-subject designs to assess individual differences in decision making phenomena such as framing effects and other biases and heuristics is recommended for future research.

Abstract not found

We focus on an affective aspect of communications by e-mail. In this study university students communicated their information to anonymous companions by e-mail to examine the relations between their affective traits, affective states and affective interpretations. Before the e-mail communication, as the affective traits, they were asked to give the frequencies of 12 affects that they experienced every day. Then, whenever they received the e-mails, using questionnaires, we asked them as follows: (1) what affect they produced: affective states (2) how they interpreted companions' affect: affective interpretations. By the result of the factor analysis of the data of the affective traits, the subjects divided into the three groups: group of "Negative Affects", "Positive Affects" and "Affects of Enemies". The subjects in each group were compared about the correlation between the affective interpretations and states. We found that in communications by e-mail when the subjects interpreted their companions' affective states as positive affective states, they might tend to feel positive affects. But, when they interpreted their companions' affective states as negative affects, their affective states might be influenced by their affective traits. This may demonstrate that the affective traits influence on our affective states in e-mail communications.

As research has revealed the deep role that emotion and emotion expression play in human social interaction, researchers in human-computer interaction have proposed that more effective human-computer interfaces can be realized if the interface models the user’s emotion as well as expresses emotions. Affective computing was defined by Rosalind Picard

Affect has been the subject of increasing attention in cognitive accounts of learning. Many intelligent tutoring systems now seek to adapt pedagogy to student affective and motivational processes in an effort to increase the effectiveness of tutorial interaction and improve learning outcomes. To this end, recent work has begun to investigate the emotions experienced during learning in a variety of environments. In this paper we extend this line of research by investigating the affective transitions that occur throughout narrative-centered learning experiences. Further analysis differentiates the likelihood of affective transitions stemming from pedagogical agent empathetic responses to student affect.

Fictional characters (FCs) and mediated persons in literature, theater, film, art, TV, and digital media fulfil basic psychological functions, although the processes involved remain unspecified. Departing from identification and empathy hypotheses, a new context-sensitive model draws upon similarity studies, empirical aesthetics, persuasion, emotion and social psychology. The PEFiC-model (Perceiving and Experiencing Fictional Characters) has three phases. During encoding, observers judge FCs in terms of ethics (good-bad), aesthetics (beautiful-ugly), and epistemics (realistic-unrealistic). Comparison entails appraisals of personal relevance as well as valence towards and (dis)similarity between the dramatis personae and the self. In the response phase, appreciation of FCs is a trade-off between the parallel, unipolar processes of involvement and distance. Intricate involvement-distance conflicts occur when subjective norms disagree with ingroup norms. Furthermore, features participate in multiple (fuzzy) sets (e.g., partly good and partly bad). PEFiC can handle complex responses towards representations of (non-existent) others, such as attractive dissimilarity, the beauty in ugliness, the appeal of negative experiences, and fascination for evil, as well as mixed emotions, ambivalence, and neutral end states that actually conceal emotional confusion. Key words: Motion pictures, involvement, media, fiction, aestheticsPerceiving and Experiencing.. 3