Surprise

About: Surprise is a research topic. Over the lifetime, 4371 publications have been published within this topic receiving 99386 citations.

Playing twenty questions with nature (the surprise version): reflections on the dynamics of experience

Abstract: It is a common complaint that the science of cognition does not do justice to either the reality of cognition in the wild or to the demands of engineering socio-technical systems. This article draws on examples from early functionalist/pragmatist views in psychology, modern physics and dynamical systems theory to explore the ontological basis of this complaint. Tentative steps are made toward a new way to frame an ontology of experience. In this framework, the duality (complementary nature) of control and observation is offered as an alternative to the dichotomy (independent nature) of mind and matter.

An Emotion Care Model using Multimodal Textual Analysis on COVID-19.

Abstract: At the dawn of the year 2020, the world was hit by a significant pandemic COVID-19, that traumatized the entire planet. The infectious spread grew in leaps and bounds and forced the policymakers and governments to move towards lockdown. The lockdown further compelled people to stay under house arrest, which further resulted in an outbreak of emotions on social media platforms. Perceiving people's emotional state during these times becomes critically and strategically important for the government and the policymakers. In this regard, a novel emotion care scheme has been proposed in this paper to analyze multimodal textual data contained in real-time tweets related to COVID-19. Moreover, this paper studies 8-scale emotions (Anger, Anticipation, Disgust, Fear, Joy, Sadness, Surprise, and Trust) over multiple categories such as nature, lockdown, health, education, market, and politics. This is the first of its kind linguistic analysis on multiple modes pertaining to the pandemic to the best of our understanding. Taking India as a case study, we inferred from this textual analysis that 'joy' has been lesser towards everything (~9-15%) but nature (~17%) due to the apparent fact of lessened pollution. The education system entailed more trust (~29%) due to teachers' fraternity's consistent efforts. The health sector witnessed sadness (~16%) and fear (~18%) as the dominant emotions among the masses as human lives were at stake. Additionally, the state-wise and emotion-wise depiction is also provided. An interactive internet application has also been developed for the same.

Effects of Age and Task Difficulty on Recognition of Facial Affect

Abstract: Current evidence suggests that older adults are less accurate than young adults in their ability to identify facial expressions of emotion. In the present study, young and older adults' ability to correctly recognize facial affect representative of 6 different emotions (happiness, surprise, disgust, fear, anger, and sadness) was examined in 3 conditions varying in difficulty. Task difficulty was measured by varying the number of labels available in a forced choice recognition task to 2, 4, and 6. Results showed that age differences were present in the 2 more difficult conditions for fear and sadness. Older adults were impaired in recognizing facial expressions of surprise only in the 4-label condition. Current findings suggest that task difficulty moderates age differences in emotion labeling. The present study has contributed to previous research by illuminating the conditions under which age differences in the accuracy of labeling of facial affect are more likely to be observed.

Data-intensive evaluation of design creativity using novelty, value, and surprise

Abstract: The increasing availability of large quantities of product-related data provides an opportunity to augment human designers with analytical models for evaluating the creativity of a new design. In this paper we describe three characteristics of a creative design: novelty, value, and surprise. We present an analytical framework for computationally evaluating the creativity of a new design. Building on our previous work, we associate each characteristic with a computational process, and develop a new model for evaluating surprise using predictive analytics. We describe an implementation of our analytical models as applied to a data-set of mobile devices. We report on the most surprising devices identified by our models and their corresponding novelty and value scores, and conclude by discussing the broader applications and implications of an analytical approach to evaluating creative designs.