Abstract. This paper describes a corpus annotation project to study issues in the manual annotation of opinions, emotions, sentiments, speculations, evaluations and other private states in language. The resulting corpus annotation scheme is described, as well as examples of its use. In addition, the manual annotation process and the results of an inter-annotator agreement study on a 10,000-sentence corpus of articles drawn from the world press are presented.

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In this paper we present a linguistic resource for the lexical representation of affective knowledge. This resource (named WORDNET-AFFECT) was developed starting from WORDNET, through a selection and tagging of a subset of synsets representing the affective meanings. 1.

Emotions are universally recognized from facial expressions—or so it has been claimed. To support that claim, research has been carried out in various modern cultures and in cultures relatively isolated from Western influence. A review of the methods used in that research raises questions of its ecological, convergent, and internal validity. Forced-choice response format, within-subject design, preselected photographs of posed facial expressions, and other features of method are each problematic. When they are altered, less supportive or nonsupportive results occur. When they are combined, these method factors may help to shape the results. Facial expressions and emotion labels are probably associated, but the association may vary with culture and is loose enough to be consistent with various alternative accounts, 8 of which are discussed. "Everyone knows that grief involves a gloomy and joy a cheerful countenance.... There are characteristic facial expressions which are observed to accompany anger, fear, erotic excitement, and all the other passions " (Aristotle, nd/1913, pp. 805, 808). Aristotle was not proposing a new idea but was cataloging what was known on the topic of physiognomy. The theory was that a person's physical appearance, especially in the face, reveals deeper characteristics: Poor proportions reveal a rogue, soft hair a coward, and a smile a happy person.' Today, few psychologists share Aristotle's belief about the meaning of poor proportions or soft hair, but many share his beliefs about facial expression and emotion. Oatley and Jenkins (1992) observed, "By far the most extensive body of data in the field of human emotions is that on facial expressions of emotion" (p. 67). Recent reviews of those data (see Table 1) agree that the face reveals emotion in a way that is universally understood: Happiness, surprise, fear, anger, contempt, disgust, and sadness—these seven emotions, plus or minus two, are recognized from facial expressions by all human beings, regardless of their cultural background.

The affect system has been shaped by the hammer and chisel of adaptation and natural selection such that form follows function. The characteristics of the system thus differ across the nervous system as a function of the unique constraints existent at each level. For instance, although physical limitations constrain behavioral expressions and incline behavioral predispositions toward a bipolar (good—bad, approach—withdraw) organization, these limiting conditions lose their power at the level of underlying mechanisms. According to the authors ' model of evaluative space ( J. T. Cacioppo & G. G. Berntson, 1994; J. T. Cacioppo, W. L. Gardner, & G. G. Berntson, 1997), the common metric governing approach—withdrawal is generally a single dimension at response stages that itself is the consequence of multiple operations, such as the activation function for positivity (appetition) and the activation function for negativity (aversion), at earlier affective processing stages.

Affective computing is advancing as a field that allows a new form of human computer interaction, in addition to the use of natural language. There is a wide perception that the future of human-computer interaction is in themes such as entertainment, emotions, aesthetic pleasure, motivation, attention, engagement, etc. Studying the relation between natural language and affective information and dealing with its computational treatment is becoming crucial. In this paper we present a linguistic resource for a lexical representation of affective knowledge. This resource (named WORDNET-AFFECT) was developed starting from WORDNET, through the selection and labeling of the synsets representing affective concepts.

The authors investigated whether people can feel happy and sad at the same time. J. A. Russell and J. M. Carroll's (1999) circumplex model holds that happiness and sadness are polar opposites and, thus, mutually exclusive. In contrast, the evaluative space model ( J. T. Cacioppo & G. G. Berntson, 1994) proposes that positive and negative affect are separable and that mixed feelings of happiness and sadness can co-occur. The authors both replicated and extended past research by showing that whereas most participants surveyed in typical situations felt either happy or sad, many participants surveyed immediately after watching the film Life Is Beautiful, moving out of their dormitories, or graduating from college felt both happy and sad. Results suggest that although affective experience may typically be bipolar, the underlying processes, and occasionally the resulting experience of emotion, are better characterized as bivariate. Just as black is the opposite of white, happiness seems to be the opposite of sadness. The two emotions differ in almost every respect. Those who are satisfied with their current state typically feel happy; those who are dissatisfied feel sad ( Russell & Carroll, 1999). Those who get what they want feel happy; those who do not feel sad ( Shaver, Schwartz, Kirson, & O'Connor, 1987). When people are happy they generally smile, laugh, and seek out others; when they are sad they frown, cry, and withdraw from others ( Shaver et al., 1987). Given such sharp contrasts between happiness and sadness, models of affect typically conceptualize the two emotions as diametric opposites (e.g., R. J. Larsen & Diener,

We investigated the emotional response patterns and sense of presence elicited by video games with different characteristics (i.e., Tetris, Super Monkey Ball 2, Monkey Bowling 2, and James Bond 007: NightFire) among 37 undergraduates. We also examined the moderating influence of the sensation seeking and self-forgetfulness traits on the responses. Participants self-reported their emotional responses, defined in terms of joy, pleasant relaxation, anger, fear, and depressed feeling, and sense of presence. The results showed that games with different characteristics elicit differential emotional response patterns, and the engagement elicited by the games varies as a function of the Sensation Seeking trait of the player. Measuring emotional response patterns may have practical implications for game design, given that they give information on the game characteristics that maximize entertainment and pleasure, and may potentially be used in pre-testing different versions of the games. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.

This study provides insights on the trust-related factors that influence consumer intentions to use online banking. Specifically, the study examines the relationships between trustworthiness, trust, distrust, and user intentions to use online banking services. Over 500 college students located across two different universities completed a survey designed to examine the effects of trustworthiness perceptions on trust and distrust, and the downstream influence of trust and distrust on intention to use. As hypothesized, results indicate that trust and distrust are distinct constructs, and that the established nomological network between trustworthiness, trust, and intention hold in the current context. Also supported is the new contention that trustworthiness is negatively related to distrust, and that distrust has a negative effect on intention to use. Finally, our hypothesis examining the relative contribution of trust and distrust on user intentions was not supported. In the context of this study, trust overwhelmed distrust.

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