Suspense is a key narrative issue in terms of emotional gratifications. Reactions in response to this type of entertainment are positively related to enjoyment, having a significant impact on the audience's immersion and suspension of disbelief. Related to computational modelling of this feature, some automatic storytelling systems include limited implementations of suspense management system in their core. In this way, the interest of this subject in the area of creativity has resorted to different definitions from fields as narratology and the film industry, as much as several proposals of its constituent features. Among their characteristics, uncertainty is one of the most discussed in terms of impact and need: while many authors affirm that uncertainty is essential to evoke suspense, others limit or reject its influence. Furthermore, the paradox of suspense reflects the problem of including uncertainty as a component required in suspense creation systems. Due to this need to contrast the effects of the uncertainty in order to compute a general model for automatic storytelling systems, we conducted an experiment measuring suspense experienced by a group of subjects that read a story. While a group of them were told the ending of the story in advance, the members of the other group experimented the same story in chronological order. Both the subjects' reported suspense and their physiological responses are gathered and analyzed. Results provide evidence to conclude that uncertainty affects the emotional response of readers, but independently and in a different form than suspense does. It will help to propose a model in which uncertainty is processed separately as management of the amount of knowledge about the outcome available to the spectator, which acts as a control signal to modulate the input features, but not directly in suspense computing.

Comprehension of stories requires readers to take the perspective of the story characters and imagine or feel their cognitive and affective states. The study investigated how variations in emotional valence within a literary text affected readers’ global text processing, as reflected in their eye movements during the first and second-pass reading, and their memory for text. Processes of reading were also examined in relation to readers’ dispositional empathy. Undergraduate students (N = 42) were assigned to an emotionally negative or neutral reading condition. They read a natural text passage from a suspense story while their ocular behavior was registered. After reading, they responded to multiple-choice questions assessing their memory of the text. Results revealed longer first-pass fixation times for content evoking negative emotions than for neutral content, which could be suggestive of a more analytical processing of the former. These effects were however local and did not impact the processing of the text at global level. Memory for the emotionally negative content was more accurate than memory for the neutral content. Dispositional empathy did not contribute to reading processes and outcome. Findings are discussed against the mixed results in the current literature and practical implications are also outlined.

The recognition of activities of daily living is an important research area of interest in recent years. The process of activity recognition aims to recognize the actions of one or more people in a smart environment, in which a set of sensors has been deployed. Usually, all the events produced during each activity are taken into account to develop the classification models. However, the instant in which an activity started is unknown in a real environment. Therefore, only the most recent events are usually used. In this paper, we use statistics to determine the most appropriate length of that interval for each type of activity. In addition, we use ontologies to automatically generate features that serve as the input for the supervised learning algorithms that produce the classification model. The features are formed by combining the entities in the ontology, such as concepts and properties. The results obtained show a significant increase in the accuracy of the classification models generated with respect to the classical approach, in which only the state of the sensors is taken into account. Moreover, the results obtained in a simulation of a real environment under an event-based segmentation also show an improvement in most activities.

Suspense is a key narrative issue in terms of emotional gratification, influencing the way in which the audience experiences a story. Virtually all narrative media uses suspense as a strategy for reader engagement regardless of the technology or genre. Being such an important narrative component, computational creativity has tackled suspense in a number of automatic storytelling. These systems are mainly based on narrative theories, and in general lack a cognitive approach involving the study of empathy or emotional effect of the environment impact. With this idea in mind, this paper reports on a computational model of the influence of decorative elements on suspense. It has been developed as part of a more general proposal for plot generation based on cognitive aspects. In order to test and parameterise the model, an evaluation based on textual stories and an evaluation based on a 3D virtual environment was run. In both cases, results suggest a direct influence of emotional perception of decorative objects in the suspense of a scene.

The emotional response to a stimulus is typically measured in three variables called valence, arousal and dominance. Based on such dimensions, Bradley and Lang (1999) published the Affective Norms for English Words (ANEW), a corpus of affective ratings for 1,034 non-contextualized words. Expanded and adapted to many languages, ANEW provides a corpus to evaluate and to predict human responses to different stimuli, and it has been used in a number of studies involving analysis of emotions. However, ANEW seems not to appropriately predict affective responses to concepts when these are contextualized in certain situational backgrounds, in which words can have different connotations from those in non-contextualized scenarios. These contextualized affective norms have not been sufficiently contrasted yet because the literature does not provide a corpus of the ANEW list in specific contexts. On this basis, this paper reports on the creation of a new corpus of affective norms for the original 1,034 ANEW words in a particular context (a fictional scene of suspense). An extensive quantitative data analysis comparing both corpora was carried out, confirming that the affective ratings are highly influenced by the context. The corpus can be downloaded as Supplementary Material.