What is eSports and why do people watch it
TL;DR: In this article, the authors investigate why people spectate eSports on the internet and find that escapism, acquiring knowledge about the games being played, novelty and eSports athlete aggressiveness positively predict eSport spectating frequency.
Abstract: The purpose of this paper is to investigate why do people spectate eSports on the internet. The authors define eSports (electronic sports) as “a form of sports where the primary aspects of the sport are facilitated by electronic systems; the input of players and teams as well as the output of the eSports system are mediated by human-computer interfaces.” In more practical terms, eSports refer to competitive video gaming (broadcasted on the internet).,The study employs the motivations scale for sports consumption which is one of the most widely applied measurement instruments for sports consumption in general. The questionnaire was designed and pre-tested before distributing to target respondents (n=888). The reliability and validity of the instrument both met the commonly accepted guidelines. The model was assessed first by examining its measurement model and then the structural model.,The results indicate that escapism, acquiring knowledge about the games being played, novelty and eSports athlete aggressiveness were found to positively predict eSport spectating frequency.,During recent years, eSports (electronic sports) and video game streaming have become rapidly growing forms of new media in the internet driven by the growing provenance of (online) games and online broadcasting technologies. Today, hundreds of millions of people spectate eSports. The present investigation presents a large study on gratification-related determinants of why people spectate eSports on the internet. Moreover, the study proposes a definition for eSports and further discusses how eSports can be seen as a form of sports.
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01 Jan 2020
TL;DR: This article evaluates the first professional-level prediction models for live DotA 2 matches, one of the most popular MOBA games, and trials it at a major international esports tournament, highlighting the need for algorithm evaluation and optimization.
Abstract: Esports are competitive videogames watched by audiences. Most esports generate detailed data for each match that are publicly available. Esports analytics research is focused on predicting match outcomes. Previous research has emphasised pre-match prediction and used data from amateur games, which are more easily available than professional level. However, the commercial value of win prediction exists at the professional level. Furthermore, predicting real-time data is unexplored, as is its potential for informing audiences. Here we present the first comprehensive case study on live win prediction in a professional esport. We provide a literature review for win prediction in a multi-player online battle arena (MOBA) esport. The paper evaluates the first professional-level prediction models for live DotA 2 matches, one of the most popular MOBA games and trials it at a major international esports tournament. Using standard machine learning models, feature engineering and optimization, our model is up to 85\% accurate after 5 minutes of gameplay. Our analyses highlight the need for algorithm evaluation and optimization. Finally, we present implications for the esports/game analytics domains, describe commercial opportunities, practical challenges, and propose a set of evaluation criteria for research on esports win prediction.
52 citations
06 May 2017
TL;DR: This paper critically reviewed existing definitions/understandings of eSports in different disciplines and interviews 26 eSports players to explore diverse perspectives on what defines eSports as a starting point for further research.
Abstract: This paper represents our first endeavor to explore how to better understand the complex nature, scope, and practices of eSports. Our goal is to explore diverse perspectives on what defines eSports as a starting point for further research. Specifically, we critically reviewed existing definitions/understandings of eSports in different disciplines. We then interviewed 26 eSports players and qualitatively analyzed their own perceptions of eSports. We contribute to further exploring definitions and theories of eSports for CHI researchers who have considered online gaming a serious and important area of research, and highlight opportunities for new avenues of inquiry for researchers who are interested in designing technologies for this unique genre.
49 citations
TL;DR: Extreme real-life social withdrawal and IGD are related, and this association is exacerbated for those who spend more time playing MMOs per day, and, for Australian participants, living with their parents.
47 citations
TL;DR: The findings indicated that the imagination group was statistically different when compared to thephysical enactment and the sport simulation groups, however, the physical enactment group and theSport simulation group were found to be similar.
46 citations
TL;DR: There has been a rapid increase, on a global scale, in the popularity of Esports worldwide, evidenced by the exponential growth in participation, media coverage, viewership, sponsorship, and commercialization.
45 citations
References
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TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Abstract: The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addit...
56,555 citations
TL;DR: In this paper, the authors provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development, and present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests.
Abstract: In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We discuss the comparative advantages of this approach over a one-step approach. Considerations in specification, assessment of fit, and respecification of measurement models using confirmatory factor analysis are reviewed. As background to the two-step approach, the distinction between exploratory and confirmatory analysis, the distinction between complementary approaches for theory testing versus predictive application, and some developments in estimation methods also are discussed.
34,720 citations
TL;DR: In this article, the authors address the ability to predict peoples' computer acceptance from a measure of their intentions, and explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables.
Abstract: Computer systems cannot improve organizational performance if they aren't used. Unfortunately, resistance to end-user systems by managers and professionals is a widespread problem. To better predict, explain, and increase user acceptance, we need to better understand why people accept or reject computers. This research addresses the ability to predict peoples' computer acceptance from a measure of their intentions, and the ability to explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables. In a longitudinal study of 107 users, intentions to use a specific system, measured after a one-hour introduction to the system, were correlated 0.35 with system use 14 weeks later. The intention-usage correlation was 0.63 at the end of this time period. Perceived usefulness strongly influenced peoples' intentions, explaining more than half of the variance in intentions at the end of 14 weeks. Perceived ease of use had a small but significant effect on intentions as well, although this effect subsided over time. Attitudes only partially mediated the effects of these beliefs on intentions. Subjective norms had no effect on intentions. These results suggest the possibility of simple but powerful models of the determinants of user acceptance, with practical value for evaluating systems and guiding managerial interventions aimed at reducing the problem of underutilized computer technology.
21,880 citations
01 Jan 1998
10,147 citations
TL;DR: A new latent variable modeling approach is provided that can give more accurate estimates of interaction effects by accounting for the measurement error that attenuates the estimated relationships.
Abstract: The ability to detect and accurately estimate the strength of interaction effects are critical issues that are fundamental to social science research in general and IS research in particular. Within the IS discipline, a significant percentage of research has been devoted to examining the conditions and contexts under which relationships may vary, often under the general umbrella of contingency theory (cf. McKeen et al. 1994, Weill and Olson 1989). In our survey of such studies, the majority failed to either detect or provide an estimate of the effect size. In cases where effect sizes are estimated, the numbers are generally small. These results have led some researchers to question both the usefulness of contingency theory and the need to detect interaction effects (e.g., Weill and Olson 1989). This paper addresses this issue by providing a new latent variable modeling approach that can give more accurate estimates of interaction effects by accounting for the measurement error that attenuates the estimated relationships. The capacity of this approach at recovering true effects in comparison to summated regression is demonstrated in a Monte Carlo study that creates a simulated data set in which the underlying true effects are known. Analysis of a second, empirical data set is included to demonstrate the technique's use within IS theory. In this second analysis, substantial direct and interaction effects of enjoyment on electronic-mail adoption are shown to exist.
5,639 citations