This paper aims to provide clarity and a sense of understanding of the usage of emotes in chats on the platform Twitch.tv. It can be assumed that emotes are used to either build on the meaning of the message, in terms of providing what facial expressions provide in face-to-face conversations, to indicate irony or in other ways to add meaning to the message, or as a mitigating function as illocutionary force indicators.
The paper will accomplish this by first giving an oversight of previously done research related to the topic. Then it will explain how the data was collected and how it is going to be used for this paper. A summary of the results gained from processing the data will be presented before those results will be discussed. Lastly, the paper will conclude with an evaluation of the accuracy of the hypothesis.
During the pandemic, the need for entertainment that was easy to come by and accessible from home was at an all-time high. Many platforms offering video on demand (VOD) services profited greatly from this newfound demand. But not only did the demand for platforms offering VOD services grow, but also the need for live entertainment. For many, the solution was the live streaming platform Twitch.
Table of Contents
1. Introduction
2. Theoretical background
2.1. Computer Mediated Communication (CMC)
2.2. Emoticons, Emotes and what illocution has to do with all this
2.3. Twitch
3. Methodology
4. Results & Discussion
4.1. Which emotes and from where?
4.2. LETSGO
4.3. KEKW
4.4. Awkward
4.5. Drake
4.6. OMEGALUL
4.7. Quantified results
5. Conclusion
Research Objectives and Core Themes
This paper investigates the pragmatic functions and usage patterns of popular emotes within Twitch.tv chats to understand how digital symbols replace non-verbal communication in live-streaming environments. By applying speech act theory, it examines whether these emotes function as emotional indicators, instruments of irony, or illocutionary force indicators.
- Linguistic analysis of non-verbal communication in computer-mediated environments.
- Categorization of Twitch emotes based on Dresner and Herring’s functional framework.
- Evaluation of emotes through the lens of Searle’s theory of illocutionary speech acts.
- Empirical analysis of chat data from prominent streamers to observe emote usage frequency and context.
- Investigation into how digital symbols mitigate or clarify the intent behind textual utterances in live chat.
Excerpt from the Book
1. Introduction
During the pandemic, the need for entertainment that was easy to come by and accessible from home was at an all-time high. Many platforms offering video on demand (VOD) services profited greatly from this newfound demand. But not only did the demand for platforms offering VOD services grow, but also the need for live entertainment.
For many, the solution was the live streaming platform Twitch. By offering the possibility for real-time interaction with the streamer and the other viewers Twitch quickly amassed a vast number of viewers overall categories. In only one year they had more than doubled the number of average viewers. From before the pandemic in January 2020 to the same month in the following year, the number grew from approximately 1.35 million to just under three million (Twitch Statistics & Charts, n.y.).
Even though there has been substantial interest in Twitch due to its increasing popularity among all demographics, there is still research that needs to be done. The usage of emotes, which are a vital part of Twitch culture, needs to be analysed more, as they are often used in unintuitive ways.
This paper aims to do just that and provide clarity and a sense of understanding of the usage of emotes in chats on the platform Twitch.tv.
Summary of Chapters
1. Introduction: Discusses the rise of Twitch during the pandemic and establishes the research goal to analyze the pragmatic function of emotes in live chat environments.
2. Theoretical background: Explores Computer Mediated Communication (CMC), Twitch as a platform, and outlines theoretical frameworks like illocutionary acts and non-verbal signal functions.
3. Methodology: Details the corpus compilation process, including data downloading from selected streams and the systematic analysis of emotes using quantitative and qualitative methods.
4. Results & Discussion: Presents the findings regarding specific emotes, their contextual usage patterns, and how they function as illocutionary speech acts supported by captured chat excerpts.
5. Conclusion: Summarizes that emotes primarily function as replacements for facial expressions rather than extensions of meaning and evaluates the paper's original hypothesis.
Keywords
Twitch, Emotes, Computer Mediated Communication, CMC, Illocutionary Force, LETSGO, KEKW, Awkward, Drake, OMEGALUL, Speech Acts, Pragmatics, Live Streaming, Digital Communication, Sentiment Analysis
Frequently Asked Questions
What is the primary focus of this research?
The work focuses on analyzing how emotes are used as tools for communication in Twitch chats, specifically exploring their pragmatic functions and how they replace traditional non-verbal cues.
Which specific emotes are investigated in the study?
The study specifically examines five popular BTTV and Twitch-native emotes: KEKW, LETSGO, Drake, Awkward, and OMEGALUL.
What is the main objective of this paper?
The objective is to provide a linguistic understanding of how viewers use these symbols to build on the meaning of messages, indicate irony, or clarify the illocutionary force behind their text-based utterances.
What methodology does the author employ?
The author compiled a corpus of over 148,000 chat messages from four distinct streams, manually filtering the top twenty most frequent tokens to identify the target emotes and analyzing their context.
What does the main body of the paper cover?
The main body covers the theoretical foundations of CMC and speech acts, explains the data collection process, provides a detailed discussion of emote usage per category, and analyzes findings via graphs and chat excerpts.
Which theoretical frameworks are used for analysis?
The research primarily relies on Dresner and Herring’s classification of non-verbal functions in CMC and John Searle’s theory of illocutionary speech acts.
How does the usage of the "Awkward" emote relate to irony?
The study identifies that "Awkward" is frequently used when users want to indicate irony or react to bizarre statements, effectively serving as an indicator of a joke rather than just expressing discomfort.
How are emote variations like "OMEGALUL" categorized?
These are categorized as expressive speech acts because they serve to convey the user's amusement and enjoyment within the situational context of the live chat.
- Arbeit zitieren
- Janne Siebertz (Autor:in), 2022, Linguistic analysis of the usage of emotes in Twitch Chat, München, GRIN Verlag, https://www.grin.com/document/1309112
