Maria Augusta Silveira Netto Nunes

Personality in Social Group Dynamics

The concept of personality has been used in multiagentsystems to create diversity in the behaviours of autonomousagents. This diversity is useful to explore different strategies in societies of agents, for example, to form coalitions, and is essential to model natural and “human-like” social agents. In the case of agents that interact with users, personality becomes a core issue and is one of the main drives to achieve the users’ suspension of disbelief. This paper presents a computational model of personality based on the Five Factor Model (FFM) of personality that generates diversity in the behaviour of social agents that interact in teamwork scenarios.

Approaches for Generating Empathy: A Systematic Mapping

Empathy plays an important role in social interactions, such an effective teaching-learning process in a teacher-student relationship, and company-client or employee-customer relationship to retain potential clients and provide them with greater satisfaction. Increasingly, people are using technology to support their interactions, especially when the interlocutors are geographically distant from one another. This has a negative impact on the empathic capacity of individuals. In the Computer Science, there are different approaches, techniques and mechanisms to promote empathy in social or human-computer interactions. Therefore, this article presents a systematic mapping to identify and systematize the approaches, techniques and mechanisms used in computing to promote empathy. As a result, we have identified existing approaches (e.g. collaborative learning environment, virtual and robotics agents, and collaborative/affective games) to promote empathy, the main areas involved (e.g. human-computer interaction, artificial intelligence, robotics, and collaborative systems), the top researchers and their affiliations who are potential contributors to future research and, finally, the growth status of this line of research.

Mining on Line General Opinions About Sustainability of Hotels: A Systematic Literature Mapping

Context: Nowadays, people do not only navigate, but also contribute content to the Internet. Thoughts and opinions are written on rating sites, forums, social networks, blogs and other media. Such opinions constitute a valuable source of information for companies, governs and consumers, but it would be humanly impossible to analyze and locate the opinions in those assessments, due to the large volume and different origins of the data. For this, approaches and techniques of opinion mining in texts are used. Objective: To identify and characterize the techniques used for mining data in public opinion repositories regarding hotels, since the opinion mining area has offered necessary subsidies for decision-making related to hotel management. Besides, to identify, specifically, studies that investigated the opinions about the sustainability of hotels. Method: A systematic mapping was performed to characterize the research area. Results: It was identified that, among the main approaches, 31% of the works found use only data mining, while 55% exclusively use machine learning techniques, and 14% both. Conclusion: The most relevant studies in such research lines adopt machine learning algorithms such as Naive Bayes, SVM, LDA, decision tree, besides aspect-based techniques and SentiWordNet lexicon dictionaries. There are still opportunities to explore opinion mining solutions in online hotel reviews, mainly by taking into consideration aspects related to sustainable practices and sustainability levels practiced by each hotel.

Social interactions and emotional contagion in virtual learning environments: An interdisciplinary approach

This article presents the state of the art in an interdisciplinary vision of the concept emotional contagion from systematic mapping method. It proposes a socio-affective model to infer certain mood in a class group. The aim is to support studies to develop technologies able to identify socio-affective processes in computer systems in the context of education. Nowadays, when interpersonal exchanges are intensely held in computerized environments, the survey conducted in the scientific literature reveals great interest on the psychological concept. However, this concept is little explored in technologies for teaching and learning environments.

Evaluation between humans and affective NPC in digital gaming scenario

The scenario of affective computing has expanded into different areas, demonstrating its applicability in various fields and specific scenarios. The area of digital games, in particular serious games, is one of the areas that can benefit from the use of affective computing, especially when used in artificial intelligence agents, also defined as NPC (Non-Player Character) simulating human affective aspects such as personality, emotion and mood. Many advances have been made for combining affective computing and serious games. However, since games present a direct interaction with the user, they require more attention to one important factor: the fun factor provided by the game. This paper aims at evaluating the fun factor of a game by experiencing a memory game that makes use of affective agent as a NPC opponent. The results in this paper demonstrate significant advances in the ability to simulate affective NPC agent in games toward modifying the way in which players analyze a current NPC and mainly at the level of pleasure dueling it.