Cross-cultural comparison of interactive streaming services: Evidence from Twitch

Oh, Soyoung; Kim, Jina; Ji, Honggeun; Park, Eunil; Han, Jinyoung; Ko, Minsam; Lee, Munyoung

doi:10.1016/j.tele.2020.101434

Cited by 17 publications

(27 citation statements)

References 15 publications

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“…However, further empirical evidence is needed for a more in-depth understanding of user behaviour. In their intercultural analysis, Oh et al [ 39 ] found significant differences between Eastern and Western culture in various linguistic and psychological dimensions. In this regard, there have been relatively few studies that account for the possible impact on user behaviour of variables that may be a source of heterogeneity in the sample.…”

Section: Literature Reviewmentioning

confidence: 99%

Motivations for the Use of Video Game Streaming Platforms: The Moderating Effect of Sex, Age and Self-Perception of Level as a Player

Cabeza-Ramírez

Sánchez‐Cañizares

García

2020

IJERPH

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A particularly striking new phenomenon in recent years is the live streaming of video games through popular platforms, such as Twitch. This study focuses on the motivations and types of use underlying viewer participation in live streaming platforms. Based on the uses and gratifications theory, this paper aims to analyse how three basic motivations are related to the use of video game streaming platforms. Furthermore, it examines the moderating effects that significant variables, such as the audience member’s age, sex or self-perception of level as a player may exert on this relationship. The results reveal that the three types of motivations are positively associated with use of the platform, although notable differences appear, with informational motivations outweighing entertainment and social motivations. At the same time, no moderating effects on the results of the proposed model were found for the heterogeneity stemming from sex and age. Conversely, the influence of informational motivations on the use of these platforms is moderated by the self-perception of level as a player.

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Section: Literature Reviewmentioning

confidence: 99%

Motivations for the Use of Video Game Streaming Platforms: The Moderating Effect of Sex, Age and Self-Perception of Level as a Player

Cabeza-Ramírez

Sánchez‐Cañizares

García

2020

IJERPH

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“…Of the three components suggested by Hamilton et al (2014) , many studies on Twitch have focused on the chat feature ( Diwanji et al, 2020 ; Oh et al, 2020 ). It is not only because of the availability of the text data but also because the chat texts are a feature that can distinguish Twitch from other social media platforms.…”

Section: Literature Reviewmentioning

confidence: 99%

“…With that being said, the specific way to analyze the texts in a computational language, namely Natural Language Processing (NLP), can vary across researchers. Nonetheless, it is worth noting that a substantial proportion of the studies has selected the rule-based (dictionary-based) approach ( Diwanji et al, 2020 ; Kobs et al, 2020 ; Oh et al, 2020 ). This is somewhat surprising given that the general trend of NLP research has been using more and more complex machine learning and deep learning techniques by supervised learning such as word embedding (which represents words as dense vectors; Baden et al, 2020 ; Levy & Goldberg, 2014 ; Li & Yang, 2018 ) or unsupervised learning such as Latent Dirichlet Allocation (LDA; Maier et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Since its launch in 2011, a considerable body of research has explored communication on Twitch across diverse disciplines ( Diwanji et al, 2020 ; Hamilton et al, 2014 ; Leith, 2021 , pp. 1–19; Oh et al, 2020 ; Sjöblom & Hamari, 2017 ). While the earlier studies are more focused on introducing the platform as a new type of media ( Hamilton et al, 2014 ) or examining users' motivation to visit the platform ( Sjöblom & Hamari, 2017 ), recent studies have explored a variety of phenomena on Twitch based on its unique media form ( Diwanji et al, 2020 ; Leith, 2021 , pp.…”

Section: Introductionmentioning

confidence: 99%

“…While the earlier studies are more focused on introducing the platform as a new type of media ( Hamilton et al, 2014 ) or examining users' motivation to visit the platform ( Sjöblom & Hamari, 2017 ), recent studies have explored a variety of phenomena on Twitch based on its unique media form ( Diwanji et al, 2020 ; Leith, 2021 , pp. 1–19; Oh et al, 2020 ). However, to our best knowledge, none of them has explored how a society-level event is manifested in Twitch.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sharing emotion while spectating video game play: Exploring Twitch users' emotional change after the outbreak of the COVID-19 pandemic

Chae

Lee

2022

Computers in Human Behavior

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This paper examines how the COVID-19 pandemic associates with Twitch users' emotion, using natural language processing (NLP) as a method. Two comparable sets of text data were collected from Twitch internet relay chats (IRCs): one after the outbreak of the pandemic and another one before that. Positive emotion, negative emotion, and attitude to social interaction were tested by comparing the two text sets via a dictionary-based NLP program. Particularly regarding negative emotion, three negative emotions⸻anger, anxiety, and sadness⸻were measured given the nature of the pandemic. The results show that users' anger and anxiety significantly increased after the outbreak of the pandemic, while changes in sadness and positive emotion were not statistically significant. In terms of attitude to social interaction, users used significantly fewer “social” words after the outbreak of the pandemic than before. These findings were interpreted considering the nature of Twitch as a unique live mixed media platform, and how the COVID-19 pandemic is different from previous crisis events was discussed based on prior literature.

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A text mining-based framework to discover the important factors in text reviews for predicting the views of live streaming

Chen

Pan

2021

Applied Soft Computing

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Cross-cultural comparison of interactive streaming services: Evidence from Twitch

Cited by 17 publications

References 15 publications

Motivations for the Use of Video Game Streaming Platforms: The Moderating Effect of Sex, Age and Self-Perception of Level as a Player

Motivations for the Use of Video Game Streaming Platforms: The Moderating Effect of Sex, Age and Self-Perception of Level as a Player

Sharing emotion while spectating video game play: Exploring Twitch users' emotional change after the outbreak of the COVID-19 pandemic

A text mining-based framework to discover the important factors in text reviews for predicting the views of live streaming

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