Player Emotions Research Articles

Experiencing the Call of Duty: Exploring Emotions in Commercial War Games

This article explores how players interpret and reflect on themes in mainstream war videogames, specifically the Call of Duty franchise. Scholars have long focused on the ideological content of war games, which is marked by increased collusion of military institutions with the gaming industry and assumptions about the influential capabilities of war games, in which player agency is often downplayed. This study builds on Lenoir and Caldwell’s (2018) observations that the interpretation of mainstream franchises should focus more on their attempts to create an “affective framework” that emphasises certain emotions in players. Through a thematic analysis of semi-structured interviews with 25 participants, this study found that participants outlined their discomfort in certain missions, to the point where they even altered their playstyle, suggesting that players often reflect critically on the aspects of war these games explore. This article concludes that mainstream franchises, like Call of Duty, should be considered complex cultural artefacts consisting of various layers of meaning. Rather than directly transmitting militaristic ideologies, these games craft an emotional aesthetic capable of exploring more controversial aspects of war. The key to understanding these franchises lies directly with the players themselves, which is why audiences should be treated as conscious agents who play an active role in drawing meaning from such an aesthetic.

Applying Artificial Intelligence for Emotional Cognition in Game Testing for Quality Assurance

Artificial intelligence (AI) is a branch of computer science that tries to develop computational tools and systems that can carry out tasks comparable to human decision-making and learning. The subject of AI is expanding quickly, and AI technology is becoming more and more significant in a variety of IT specialties. When more automated and intelligent solutions are employed instead of outdated techniques, the quantity of manpower and resources needed for game testing will be greatly decreased. The aim of this study is to find new models that will make game testing easier by utilising state-of-the-art AI techniques. In an attempt to determine the model base and algorithmic foundation for the new approach, the examination and comparison of existing theories, models, and algorithms is used to infer and identify the viability of certain current mainstream AI models and algorithms in game testing sessions. Standard software testing is not the same as game testing. Further consideration should be given to the whole gaming experience and entertainment value in addition to functional testing. User questionnaires and in-game testing are used in the current standard experience testing methodology. Artificial intelligence eliminates human aspects in emotional cognition. It may produce more objective test results while spending less money for both human and material resources by using massive data sets and its own learning and processing capabilities. This paper examines the state of AI in software testing, game creation, and emotion perception using expertise in using and applying AI approaches in game testing for quality assurance. It also demonstrates how well AI methods work for predicting player emotions during game testing. The AI testing reduces testing expenses related to labour and material resources while guaranteeing total game confidentiality before release. It also increases test accuracy and reduces the impact of subjectivity.

Structures that tilt: Understanding “toxic” behaviors in online gaming

Destructive or “toxic” behaviors in online gaming have received increased attention in recent years. These are forms of verbal harassment or behavioral misconduct which disrupt another’s experience of the game. While previous explanations have explained toxic behaviors as intentional acts of deviant individuals or a larger online “trickster” culture, this article provides empirical support for a recent “tilt”-based explanation in the literature. Toxic behavior is seen as situated within and emergent from specific social contexts—as a spur-of-the-moment loss of control (associated with the term “tilt”), triggered by contextual factors within the game. Based on interview data on the popular multiplayer game League of Legends, it is shown how weak normative and relational structures within a gaming context can lead to negative emotions in players, prompting toxic behaviors. Avenues for future research and implications for improving online social spaces are discussed.

Investigation of player emotion and instinct on racing video game using 6-11 framework (Case study: split second (2010) single player modes)

Investigation of player emotion and instinct on racing video game using 6-11 framework (Case study: split second (2010) single player modes)

Cooperative behaviors in spatial multi-game based on Hawkes processes

As for collective behaviors in reality, the occurrence of similar events in group is not independent, in which the occurrence historical events, such as frequencies, interval time, etc, would have an incentive effect on their recurrence probability. In spired by this, Hawkes process is first introduced into evolutionary game model. Different from the existing works, the game behaviors in a networked group change from certainty to probabilistic behaviors affected by historical events. Specifically, an incentive effect will occur with the occurrence of game behaviors as well as decay with the lapse of time. Based on the above probabilistic game mechanism, a multi-game model is proposed, where players are assumed to be emotional for their owned resources. In general, the results of game behaviors would determine the allocation of resources, and the owned quantities of resources would affect the emotion of players. As a feedback loop, it finally affects the game strategy of players. In experiments, the mutual effect of limited resources and game strategy based on probabilistic game mechanism is quantitatively studied. Meanwhile, a phase transition of cooperative behaviors is explored, which is mainly arising from the probabilistic game processes and the evolving emotions of players.

Multisensed Emotions as Adaptation Controllers in Human-to-Serious NeuroGames Communication

Emotion is defined (from Britannica) as a complex combination of experiences of consciousness, bodily sensation and behavior, reflecting personal significance of externally and/or internally triggered changes. As an indispensable part of human communication, emotions could be represented within the digital world as a means that could control human interaction with digital artifacts. When this is combined with gamification, a more engaging communication for the player could be established. In this article, we explore how multisensed emotions of players could be used as adaptation controllers within the emotion-adapting serious neurogames (SNGs). We first briefly describe the emotion sensing and recognition landscape, examining the emotion-source sensing and emotion inferring approaches. We then discuss the SNGs design framework and the way human-to-SNG communication is set. Additionally, we describe the way the adaptation of the SNG characteristics can be driven by the inferred emotions, towards the achievement of the desired SNG goals. In addition, we demonstrate the feasibility and design characteristics of multisensed emotion-adapting SNGs, by presenting a related application case, namely EmoSense, and evaluate its acceptance as a technological solution in the field of neurofeedback. Finally, we discuss challenges and opportunities in the field.

Emotion Design for Video Games: A Framework for Affective Interactivity

Emotionally evocative games hold great potential for both industry and our basic understanding about human affect. The question of how best games elicit and respond to player emotion brings together research from psychology, design, and human-computer interaction (HCI). However, there is much confusion regarding the nature of emotions, emotional game-player interaction, and the process of creating emotional games. This article reviews important work from relevant fields to provide an interdisciplinary model that integrates current theories and highlights conceptual gaps for relevant fields. Based on this model, we propose a methodological framework that provides a step-by-step process of developing an emotion-adaptive game. This framework is open to different models of emotion, and its modular nature allows games to adapt to developments in the science of emotion and technological innovations in emotion detection. Together, the theoretical overview and framework can help reduce the confusion that surrounds creating and researching emotions in games.

Development of a Virtual Reality Escape Room Game for Emotion Elicitation

In recent years, the role of emotions in digital games has gained prominence. Studies confirm emotions’ substantial impact on gaming, influencing interactions, effectiveness, efficiency, and satisfaction. Combining gaming dynamics, Virtual Reality (VR) and the immersive Escape Room genre offers a potent avenue through which to evoke emotions and create a captivating player experience. The primary objective of this study is to explore VR game design specifically for the elicitation of emotions, in combination with the Escape Room genre. We also seek to understand how players perceive and respond to emotional stimuli within the game. Our study involved two distinct groups of participants: Nursing and Games. We employed a questionnaire to collect data on emotions experienced by participants, the game elements triggering these emotions, and their overall user experience. This study demonstrates the potential of VR technology and the Escape Room genre as a powerful means of eliciting emotions in players. “Escape VR: The Guilt” serves as a successful example of how immersive VR gaming can evoke emotions and captivate players.

Choices, affects and trans representation: An analysis of mechanics and gameplay in Tell Me Why


 
 
 The article discusses selected aspects of the 2020 game Tell Me Why, focusing on particular gameplay mechanics pertaining to player choices and the manner in which they influence player emotions, as well as on the representation of trans experience in the game. The authors draw both on affect theory and on approaches derived from game studies concerning the presence of emotions in gameplay. In the final part of the text, trans representation in Tell Me Why is analysed and juxtaposed with the readings typically found in the game’s reviews.
 
 

Mechanizmy zarządzania emocjami w grach wideo


 
 
 The article discusses issues related to the mechanisms of managing player emotions in video games. The author presents and indicates researchers’ main findings regarding emotions and their role in human life but also the basic functions of emotions in art and video games. Games are described as a medium characterized by communicative feedback between a human (player) and a machine (game), resulting in the occurrence of strong emotional impulses during the act of playing. The article refers to and interprets research on emotional reactions while playing video games and indicates the role of emotions in the marketing positioning of games.
 
 

Player's Affective States as Meta AI Design on Augmented Reality Games

Games are considered one of the most popular entertainment forms worldwide. The interaction in the game environment makes the players addicted to playing the game. One technique to build an addicting game is utilizing the player's emotions using Meta Artificial Intelligence (AI). The player's emotions can be utilized by adjusting the game difficulty. Most of the game offers static and steady difficulty development throughout the game. This research proposes a Meta AI game design using the player's affective states. We argue that a dynamic difficulty development throughout the game will increase the player's game experiences. The player's facial expressions are utilized to extract the player's affective state information. To recognize the player's facial expressions, a Facial Expressions Recognition (FER) model was trained using VGG-16 architecture and The Indonesian Mixed Emotion Dataset (IMED) dataset in addition to a self-collected dataset. The emotions recognition model (from player's facial expressions) achieved the best validation accuracy of 99.98%. The model was implemented in the proposed Meta AI game design. The Meta AI game design proposed in this game was implemented in several game scenarios to be compared and evaluated. The proposed Meta AI game design was evaluated by 31 respondents using Game Experiences Questionnaire (GEQ). Overall, the results show that the game with Meta AI and Augmented Reality implemented significantly improved the Game Experiences Questionnaire (GEQ) score and the player's overall satisfaction compared to the other game scenarios.

RELAÇÕES ENTRE A QUALIDADE PSICOLÓGICA E O TREINAMENTO EM JOGADORES DE BASQUETEBOL

ABSTRACT Introduction Psychological monitoring and psychological intervention of basketball players has been a focus of attention in sports training. In basketball, players consume much physical energy and also much mental energy. Psychological tension and emotional changes cause basketball players to restrict their technical abilities. Objective Analyze the relationship between sport-induced mental fatigue and pre-game emotions in basketball players. Methods This paper selects 40 basketball players as research volunteers. A survey questionnaire and mathematical statistics were used to analyze the relationship between basketball players’ mental fatigue, training level, and pre-game emotions. This paper analyzes the relationship between psychological quality and training level of basketball players. Results There were significant correlations between various dimensions of sport-induced mental fatigue and basketball players’ pregame emotions. Basketball players’ pre-game self-confidence is mainly affected by training game competence and excessive energy consumption. Conclusion The psychological quality of basketball players is significantly correlated with the level of training. Athletes should pay attention to psychological quality training in sports competitions. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Emotion recognition algorithm of basketball players based on deep learning

Aiming at the problems of traditional methods of emotion recognition accuracy, long recognition time and low recognition rate, a basketball player emotion recognition algorithm based on deep learning is proposed. Based on the Emotic dataset, a basketball remote mobilisation emotion recognition dataset is constructed to realise emotion classification. The LBP method is used to extract the facial expression features in the dataset, and the KDIsomap algorithm is used to perform nonlinear dimensionality reduction on the features according to the feature extraction results. According to the deep learning algorithm, the SVM classifier is combined with the KNN classification to form an SVM-KNN classifier to recognise the emotions of basketball players. Experimental results show that the shortest recognition time of the proposed algorithm is only 4.38 s, the highest recognition accuracy rate reaches 94.2%, and the recognition rate is high, indicating that the algorithm has a certain effectiveness.

Empathy in game design - Exploring a human-centric approach in designing engaging video game experiences

The link between engagement and player emotions has been extensively explored by researchers in recent years. Empathy, which is the innate ability to accurately perceive another person’s current feelings and meanings can be broadly categorized into two main human-centric design approaches - cognitive empathy and affective empathy. Certain forms of media especially time-based media have been proven to better exploit viewers’ empathy and provide a more engaging experience when a human-centric design approach is applied. The aim of this research paper is to explore if a human-centric design approach can provide the same level if not more immersive engagement when designing video game experiences. The initial research into a human-centric design approach in video games will be obtained through an exploratory research design involving six tertiary-level students in the field of game design between the ages of 20 to 24 over a period of two weeks. The exploratory research encompassing of a semi-structured interview process with eight key questions relating to the respondent’s experience with empathy in games determined the advantages of planning and designing a game using a human-centric game design approach. The research determined that human-centric game design focusing on affective empathy provides a high possibility of a more engaging game experience that is strengthened by in-game narrative elements resulting in increased time spent in-game. This can be attributed to two main factors – firstly, a stronger player connection through direct empathy to their virtual avatars or in-game characters, regardless of the player’s moral standings and principles. Secondly, an immersive narrative structure produces a deeper player attachment toward game characters and game worlds.

Experiences of Game-Based Learning and Reviewing History of the Experience Using Player's Emotions.

In this paper, we discuss whether the history of a learning experience, containing action and emotion information, is useful for review of the experience in game-based learning using virtual space. We developed a game-based story generation system that automatically generates scripts in real time by using a player's emotions and actions. The system has two functions: a game-based experiential learning environment and automatic story generation. The system provides the player with a virtual world and a virtual tool operated by using a hand controller and a display. The system recognizes the player's real-time emotions through facial expressions, and it outputs reactions based on these emotions and actions via a knowledge-based system when the player operates the tool. Then, it outputs scripts based on the emotions and the history of actions. We evaluated the system by conducting experiments with university students as subjects. As a result, subjects found the stories generated by this system interesting because they were based on the player's experience in the game and used the player's behavioral history and emotions. If we consider this as a record of the learning experience, the learning history is an impressive record accompanied by emotions. Thus, historical information that records the actions and emotions of the learner in real time is considered effective because it allows the learner to recall his or her own experiences after the game experience. The results suggest that the historical information, including the learner's real-time actions and emotions, is helpful for review in learning. There is a possibility that experiential learning through games using virtual spaces, such as the one used in this study, will become widespread in the future. In such cases, it will be necessary to examine the learning effects of using historical information with emotions. Therefore, we believe that the results and discussions in this study will be useful for experiential learning using virtual spaces.

Customizable crying and connection: personalization and its effect on player emotion and empathy

Player choice sets video games apart from other visual media, and narrative designers work with game developers to implement tools that allow players to make choices and feel involved. Prior research focuses on games that include emotional themes and character customization, which are seen as effective ways to create empathy between player and protagonist. However, most research compares different games with various levels of customization, opening doors to several confounding variables. To address this gap, it is essential to explore how character customization and narrative context influence player emotion, character connection, morality, and engagement in a single game. This study involved participants playing a custom-built interactive fiction game demo (MOSAIC). Overall, players’ attitudes toward the demo were consistent across all three experimental groups and the control group, although character connection was higher in groups where participants were given additional story information and/or opportunities to customize the protagonist. This is a valuable step towards understanding video games and player emotion, especially considering gaming’s global presence and constant expansion.

Thai undergraduate science, technology, engineering, arts, and math (STEAM) creative thinking and innovation skill development: a conceptual model using a digital virtual classroom learning environment.

Qualitative and quantitative research methods were undertaken to examine and develop a digitally based virtual classroom learning environment (VCLE) for Thai undergraduate students’ creative thinking and innovation enhancement in science, technology, engineering, arts, and math (STEM/STEAM) disciplines. The research methodology was divided into two phases, including the synthesis and then the design of the VCLE. Also, in addition to the study’s authors, nine experts were used for the model’s development and another ten for its assessment (19 total). From their in-depth interviews and subsequent content analysis, their input of the proposed STEAM-ification process was synthesized and the data analyzed. The results revealed that the VCLE design should begin with a face-to-face, classroom learning environment in which the ‘gamification’ mechanisms were introduced and examined. This was then reinforced by moving the gamification process online outside of the classroom. Furthermore, five VCLE STEAM-ification steps were found to be particularly useful for enhancing creative thinking and student innovation. These included investigation, discovery, connections, creativity, and reflection. Moreover, we identified the gamification process as consisting of three main components. These were the ‘game mechanics,' the ‘game dynamics,' and ‘player emotions’. The ten experts agreed that the VCLE STEAM-ification creativity and innovation (C & I) process was appropriate at an ‘excellent’ level (overline{x} = 4.68, S. D. = 0.47), which has great potential in the development of Thai undergraduate student C & I skills. Also, when undertaken correctly, innovation and motivation to learn are also outcomes from both VCLE and gamification applications. Thus, when students undertook study with the VCLE STEAM-ification format, they were found to achieve higher levels of creativity and innovation than students who studied using the traditional teaching plan. These results were found to be statistically significant at the .01 level.

Guided Emotional State Regulation: Understanding and Shaping Players’ Affective Experiences in Digital Games

Designing adaptive games for individual emotional experiences is a tricky task, especially when detecting a player’s emotional state in real time requires physiological sensing hardware and signal processing software. There is currently a lack of software that can identify and learn how emotional states in games are triggered. To address this problem, we developed a system capable of understanding the fundamental relations between emotional responses and their eliciting events. We propose time-evolving Affective Reaction Models (ARM), which learn new affective reactions and manage conflicting ones. These models are then meant to provide information on how a set of predetermined game parameters (e.g., enemy and item spawning, music and lighting effects) should be adapted, to modulate the player’s emotional state. In this paper, we propose and describe a framework for modulating player emotions and the main components involved in regulating players’ affective experience. We expect our technique will allow game designers to focus on defining high-level rules for generating gameplay experiences instead of having to create and test different content for each player type.

A Call for Emotion Modeling in Interactive Storytelling

Artificial Intelligence (AI) techniques are widely used in video games. Recently, AI planning methods have been applied to maintain plot consistency in the face of player’s agency over the narrative. Combined with an automatically populated player model, such AI experience managers can dynamically create a consistent narrative tailored to a specific player. These tools help game narrative designers achieve narrative goals while affording players a choice. On the other hand, they increase the number of feasible plot branches making it more difficult for the author to ensure that each branch carries the player along a desired emotion arc. In this paper we discuss the problem and call for an extension of experience managers with player emotion models. When successful, interactive narrative can be then automatically produced to satisfy authorial goals not only in terms of specific events but also in terms of emotions evoked in the player.

Designing Story-Centric Games for Player Emotion: A Theoretical Perspective

Narratives are powerful because of their impact on our emotional experiences. Recent years have witnessed significant advances in affective computing and intelligent interaction, presenting a broad range of opportunities for enhancing the design, implementation, and adaptivity of interactive narratives. This paper presents preliminary work examining story-centric games and interactive narratives from the perspective of psychological theories of emotion, with a particular focus on player affect. We examine the sources and duration of player emotion, social facets of emotion, players’ individual differences in emotion, and meta-emotions. Recommendations and future directions for research on player emotion in interactive narratives are discussed.