Femotes is a project about brining awareness to sexism in gaming by creating emotes, a common way of expression on the streaming website Twitch.tv. The goal is to bring up a discussion in the gaming community to make minority groups of gamers more welcome in the community. The ten emotes made are a way to show support to streamers who must deal with toxic behavior and to show that we stand for equality.

Context. Social interaction between player avatars is one of the fundamentals of online multiplayer games, where text- and voice chat is used as standard methods for communication. To express emotions, players have the option to use emotes, which are text-based commands to play animations of the player’s avatar. Objectives. This study investigates if real-time facial capture could be preferred and more realistic, compared to typing emote commands to play facial animations when expressing emotions to other players. Methods. By using two methods for social interaction between players, a user study with 24 participants was conducted in a private conference room. An experiment was created where each participant tested the two methods to perform facial expressions, one consisting of typing emote commands, the other by performing with the calibrated participant’s face in real-time, with a web camera. Each participant performed and ranked the realism of each facial expression, in a survey for each method. A final survey could then determine the method that each participant had greater performance with and the method that was preferred the most. Results. The results showed that there was a difference of realism between facial expressions in both methods, where happiness was the most realistic. Disgust and sadness were however poorly rated when expressing these with the face. There was no difference of realism between the methods and which method participants preferred the most. There was however a difference in each participant’s performance with the two methods, where typing emote commands had higher performance. Conclusions. The results show that there is no difference of realism and preference, in typing emote commands to play facial animations and performing facial expressions in real-time with the face. There was, however, a difference in performing each method, where performing facial expressions with the face was the lowest. This confirms that the real-time facial capture technology needs improvements, to fully recognize and track the facial features of the human face.

No description available.

Syftet med studien var att undersöka hur olika kommunikationsmedel påverkar kortspelare, och vilken kommunikationsmetod som skulle vara mest gynnsam i olika situationer. Foruminlägg indikerar att bristen på kommunikationsmetoder i kortspel är ett problem, eftersom det begränsar social interaktion mellan spelare. Metoden var att låta två olika grupper av personer spela kortspelet UNO, både analogt och digitalt under observation, med en intervju som sedan genomfördes efter varje spelomgång. Observationsanteckningarna och de transkriberade intervjuerna analyserades senare och en slutsats kunde dras. Det verkar som att olika kommunikationsmedel påverkar spelarna på varierande sätt. För omgångarna som inkluderade verbal kommunikation verkade spelarna mer avslappnade, eftersom deras konversationer var mycket växlande och innehöll mycket skratt. Under de analoga omgångarna använde spelarna sitt kroppsspråk, fick ögonkontakt och använde mycket ansiktsuttryck, något som inte kunde ses under de digitala rundorna. Under de digitala omgångarna verkade spelarna vara mycket mer fokuserade på spelet, eftersom inga andra spelare eller miljön distraherade deras spelande. Generellt verkade humöret och humorn vara högst under omgången där spelare kommunicerade via emotes, därför är det den mest fördelaktiga kommunikationsmetoden digitalt spelande. För analogt spelande är verbal kommunikation det vanligaste och mest fördelaktiga sättet att kommunicera vid spelandet av UNO. / The aim of this study was to investigate how different means of communications affect card game players, and which communication method would be the most beneficial in different scenarios. Forum posts indicate that the lack of communication methods in card games is a problem, since it limits social interaction between players. The method was to let two different groups of people play the card game UNO, both analogous and digitally under observation, with an interview then being carried through after each game round. The observation notes and the transcribed interviews were later analyzed, and a conclusion could be drawn. It seems different means of communication do affect the players in various ways. For the rounds that included verbal communication, the players would seem more relaxed, as their conversations were highly diverse, as well as containing a lot of laughter. During the analogous rounds, players used their body language, made eye contact, and used a lot of facial expressions, something that was not present during the digital rounds. However during the digital rounds, players seemed to be a lot more focused on the game, since no other players, or the environment were distracting their play. Generally the mood and humor seemed to be the highest during the round where players communicated via emotes, hence why it is the most beneficial communication method during digital play. For analogous play, verbal communication is the most common and beneficial way of communicating while playing UNO.

This thesis explores the use of emotes in a synchronous environment where hundreds to thousands of people communicate with each other in different discourse communities. The thesis performs a study on emote use based on the frequencies they are used and their different CMC features in these communities to acquire knowledge on the contextual basis of emote use in synchronous environments. By using various corpus tools and implementing both a quantitative analysis and qualitative analysis, the results show that the frequency of messages that use emotes varies based on the discourse community that is involved in the use of the emotes. The different CMC features are covered by the basis of the discourse community’s behavior, where there is also some involvement based on the size of the different discourse communities on Twitch.