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Decision-making in human beings is affected by emotions and sentiments. The affective computing takes this into account, intending to tailor decision support to the emotional states of people. However, the representation and classification of emotions is a very challenging task. The study used customized methods of deep learning models to aid in the accurate classification of emotions and sentiments.

The present study presents affective computing model using both text and image data. The text-based affective computing was conducted on four standard datasets using three deep learning customized models, namely LSTM, GRU and CNN. The study used four variants of deep learning including the LSTM model, LSTM model with GloVe embeddings, Bi-directional LSTM model and LSTM model with attention layer.

The result suggests that the proposed method outperforms the earlier methods. For image-based affective computing, the data was extracted from Instagram, and Facial emotion recognition was carried out using three deep learning models, namely CNN, transfer learning with VGG-19 model and transfer learning with ResNet-18 model. The results suggest that the proposed methods for both text and image can be used for affective computing and aid in decision-making.

The study used deep learning for affective computing. Earlier studies have used machine learning algorithms for affective computing. However, the present study uses deep learning for affective computing.

This paper aims to present affective computing or Emotion AI in the context of work and how organizational leaders such as managers and human resource (HR) professionals can implement this technology to foster an emotionally healthy workplace.

The authors provide a current overview of affective computing technology through definitions, examples and general use cases. This is in light of the current scrutiny on artificial intelligence (AI) use broadly across society. The authors address this from a research perspective and show how this advanced AI tool can be implemented in organizations for the benefit of employees.

Affective computing or Emotion AI is still relatively unknown, and yet, it is already part of our daily lives. Emotion AI platforms have the potential to be an essential part of HR tools. It is crucial, however, to use this technology in an ethical and responsible manner.

There is little awareness and understanding of use cases of affective computing tools in organizations, particularly for the well-being of the workforce. This paper provides HR leaders, managers and researchers with an overview of the origins of the field and major considerations for responsibly implementing Emotion AI to support employee mental health.

The purpose of this paper is to map the evidence provided on the review types, and explain the challenges faced by classification techniques in sentiment analysis (SA). The aim is to understand how traditional classification technique issues can be addressed through the adoption of improved methods.

A systematic review of literature was used to search published articles between 2002 and 2014 and identified 24 papers that discuss regular, comparative, and suggestive reviews and the related SA techniques. The authors formulated and applied specific inclusion and exclusion criteria in two distinct rounds to determine the most relevant studies for the research goal.

The review identified nine practices of review types, eight standard machine learning classification techniques and seven practices of concept learning Sentic computing techniques. This paper offers insights on promising concept-based approaches to SA, which leverage commonsense knowledge and linguistics for tasks such as polarity detection. The practical implications are also explained in this review.

The findings provide information for researchers and traders to consider in relation to a variety of techniques for SA such as Sentic computing and multiple opinion types such as suggestive opinions.

Previous literature review studies in the field of SA have used simple literature review to find the tasks and challenges in the field. In this study, a systematic literature review is conducted to find the more specific answers to the proposed research questions. This type of study has not been conducted in the field previously and so provides a novel contribution. Systematic reviews help to reduce implicit researcher bias. Through adoption of broad search strategies, predefined search strings and uniform inclusion and exclusion criteria, systematic reviews effectively force researchers to search for studies beyond their own subject areas and networks.

Inspired by the dynamic changes in our daily lives enabled via quantified-self technologies and the urgent need for more studies on the human-computer interaction design mechanisms adopted by these applications, this study explores the value of user affective experience mirroring and examines the empowerment effect of meaningful gamification in a psychological self-help system (PSS) that aids people in work stress relief.

Based on an analysis of the existing systems and theories in relevant fields, we conducted mixed-method research, involving semi-structured interviews, experience sampling experiments and user bio data triangulations, to identify the benefits of user affective experience mirroring and examine the impact of visual impact metaphor–based (VIM) meaningful gamification on PSS users.

For a gamified PSS, users generally perceive VIM as arousing more feelings of enjoyment, empathy, trust and usefulness, empowering them to gain more mastery and control over their emotional well-beings, especially with relieving their occupational stress and upbringing their level of perceived happiness. Overtime, VIM-based meaningful gamification further boosts such value of a PSS.

Weaving together meaningful gamification and psychological empowerment theories, the results emphasized that successful empowerment of user through gamification in PSSs relies heavily on whether a deeper and meaningful affective connection can be established with the users, in short, “meaningful gamification for psychological empowerment”. Such an understanding, as demonstrated in our research framework, also sheds light on the design theories for persuasive technology and human influence tactics during human computer interactions.

The results of the study demonstrate to practitioners how to make the best use of gamification strategies to deeply relate to and resonate with users. Even without complicated game-play design, meaningful gamification mechanisms, such as VIM facilitate the empowerment of users while gaining their appreciation, establishing a deeper connection with them and eventually generating persuasive effects on intended future behavioural outcomes.

The effective management of work-related stress with handy tools such as a VIM-based PSS can be beneficial for many organizations and, to a large extent, the society.

This study proposed and empirically demonstrated the empowerment effect of meaningful gamification for PSS users. In this cross-disciplinary study, theories from different research domains were synthesized to develop a more thorough and multi-faceted understanding of the optimal design strategies for emerging information systems like this VIM-based PSS.

The purpose of this paper is to provide an examination of emotional experiences, particularly how they are situated in the readers’ advisory (RA) literature and the literatures from a variety of outside disciplines in order to create taxonomies of affect from this context.

The approach of this study is twofold. First, this work reviews the literature on affect in Library and Information Science (LIS) and ancillary disciplines in order to understand the definition of affect. Second, using extant taxonomies and resources noted from the literature review, taxonomies are created for three aspects of affect: emotions, tones, and associations.

This paper contextualises and defines affect for the LIS discipline. Further, a result of the work is the creation of three taxonomies through an RA lens by which affective experiences can be classified. The resulting three taxonomies focus on emotion, tone, and associations.

The taxonomies of emotion, tone, and associations can be applied to the practical work of bibliographic description, helping to expand access and organisation through an affective lens. These taxonomies of affect could be used by readers’ advisors to help readers describe their desired reading experiences. As the taxonomies have been constructed from an RA perspective, and can be applied to the RA literature, they could expand the understanding of RA theory, especially that of appeal.

This study furthers the exploration of affect in LIS and provides tangible taxonomies of affect for the LIS discipline in an RA context, which have not been previously produced.

This paper examines the acceptance, of a group of 79 students, of an educational forum, used for mobile and distance learning, that has been modified to include empathic characteristics and affective principles.

With this study is proposed that the introduction of empathic and affective principles in educational forums is a useful and effective way to increase students’ participation and motivation in educational contexts. After an analysis of existing literature and research on the subject of empathic technology, the unified theory of acceptance and use of technology (UTAUT) was used as a framework for the research model. The analysis of their acceptance is done via an extended version of the UTAUT that focuses on the use of the variable attitude toward technology and uses gender, age and experience as moderators. A partial least square technique has been used to test the nine hypotheses.

The results confirmed three of the nine hypotheses: performance expectancy and effort expectancy had a positive influence on the students attitudes towards empathic forums, while the effect of social influence and facilitating conditions was considered insignificant; social influence had a positive influence on the students’ behavioral intention to use emphatic forums, while attitude toward technology, performance expectancy, facilitating conditions and effort expectancy were considered not relevant.

The focus of this study was the influence of attitude toward empathic forums, used for mobile and distance learning, and the results establish the grounds for future research on attitude as an important determinant of technology acceptance.

The purpose of this paper is to criticise ad hoc approaches to ethics in research and development in technology as descriptive and non‐ethical, and based upon a narrow conception of rationality.

The approach deploys a theory of normativity that can incorporate values and a broad conception of rationality, in order to account for the relevance of issues for the addressees of normative injunctions.

A normative approach is possible and required in order to implement ethics in research and development in technology.

The approach draws together themes from current alternative approaches that each fail to deploy the full resources of the normative approach, and so fail to fully account for ethics. This approach identifies and moves beyond present limited approaches.

This article’s purpose is to develop The Model for Smart, Self-learning and Adaptive Resilience Building (SARB).

Products and patents of methods and systems analysis was carried out in the fields of BIM application, Smart, Self-learning and Adaptive Resilience Building. Based on other researchers’ findings, The SARB Model was proposed.

Analysis of the literature showed that traditional decisions on the informational modelling do not satisfy all the needs of smart building technologies owing to their static nature. The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life.

The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life. The SARB Model does have some limitations: (1) the processes followed require the collection of much unstructured and semi-structured data from many sources, along with their analyses to support stakeholders in decision-making; (2) stakeholders need to be aware of the broader context of decision-making and (3) the proposal is process-oriented, which can be a disadvantage during the model’s implementation.

Two directions can be identified for the practical implications of the SARB Model. The initial expectation is the widespread installation of SARB Model within real estate and construction organisations. Furthermore, development of the SARB Model will be used to implement the ERASMUS+ project, “Advancing Skill Creation to ENhance Transformation—ASCENT” Project No. 561712-EPP-1-2015-UK-EPPKA2-CBHE-JP.

The practical implications of this paper are valuable.

The purpose of this paper is to explore the role of emotion in learning, specifically, e‐learning and its relationship to the phenomenon called energetic learning.

After first presenting operation definitions, the paper looks through the lens of new findings in neuroscience to build an understanding of the role of emotions in learning, then focuses specifically on how e‐learning systems contribute to energetic learning, providing examples of e‐learning platforms and software programs currently available that have specific attributes contributing to energetic learning.

With technology comes a natural excitement in terms of connectivity and its support of self‐driven, experiential learning which is part of the evolutionary heritage. As the understanding of the neuroscience and biology of human learning advances, the personal needs of individual learners are being begun to understand better. Bringing these needs together with e‐learning system capabilities will offer a significant jump in the learning rate and efficiency as we move into a future filled with change, uncertainty, complexity and anxiety.

The paper introduces the concept of energetic learning with specific focus on the contribution of e‐learning to energetic learning.