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Watch me playing, I am a professional: a first study on video game live streaming

Identifieur interne : 001B32 ( Main/Exploration ); précédent : 001B31; suivant : 001B33

Watch me playing, I am a professional: a first study on video game live streaming

Auteurs : Mehdi Kaytoue [Brésil] ; Arlei Silva [Brésil] ; Loïc Cerf [Brésil] ; Wagner Meira [Brésil] ; Chedy Raïssi [France]

Source :

RBID : Hal:hal-00697150

English descriptors

Abstract

"Electronic-sport" (E-Sport) is now established as a new entertainment genre. More and more players enjoy streaming their games, which attract even more viewers. In fact, in a recent social study, casual players were found to prefer watching professional gamers rather than playing the game themselves. Within this context, advertising provides a significant source of revenue to the professional players, the casters (displaying other people's games) and the game streaming platforms. For this paper, we crawled, during more than 100 days, the most popular among such specialized platforms: Twitch.tv. Thanks to these gigabytes of data, we propose a first characterization of a new Web community, and we show, among other results, that the number of viewers of a streaming session evolves in a predictable way, that audience peaks of a game are explainable and that a Condorcet method can be used to sensibly rank the streamers by popularity. Last but not least, we hope that this paper will bring to light the study of E-Sport and its growing community. They indeed deserve the attention of industrial partners (for the large amount of money involved) and researchers (for interesting problems in social network dynamics, personalized recommendation, sentiment analysis, etc.).

Url:
DOI: 10.1145/2187980.2188259


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<orgName>Centre National de la Recherche Scientifique</orgName>
<orgName type="acronym">CNRS</orgName>
<date type="start">1939-10-19</date>
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<ref type="url">http://www.cnrs.fr/</ref>
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<country>France</country>
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<settlement type="city">Nancy</settlement>
<settlement type="city">Metz</settlement>
<region type="region" nuts="2">Grand Est</region>
<region type="old region" nuts="2">Lorraine (région)</region>
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<orgName type="university">Université de Lorraine</orgName>
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<term>E-sport</term>
<term>Popularity prediction</term>
<term>Ranking</term>
<term>Social com- munity</term>
<term>StarCraft II</term>
<term>Twitch.tv</term>
<term>Video game</term>
</keywords>
</textClass>
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<front>
<div type="abstract" xml:lang="en">"Electronic-sport" (E-Sport) is now established as a new entertainment genre. More and more players enjoy streaming their games, which attract even more viewers. In fact, in a recent social study, casual players were found to prefer watching professional gamers rather than playing the game themselves. Within this context, advertising provides a significant source of revenue to the professional players, the casters (displaying other people's games) and the game streaming platforms. For this paper, we crawled, during more than 100 days, the most popular among such specialized platforms: Twitch.tv. Thanks to these gigabytes of data, we propose a first characterization of a new Web community, and we show, among other results, that the number of viewers of a streaming session evolves in a predictable way, that audience peaks of a game are explainable and that a Condorcet method can be used to sensibly rank the streamers by popularity. Last but not least, we hope that this paper will bring to light the study of E-Sport and its growing community. They indeed deserve the attention of industrial partners (for the large amount of money involved) and researchers (for interesting problems in social network dynamics, personalized recommendation, sentiment analysis, etc.).</div>
</front>
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<list>
<country>
<li>Brésil</li>
<li>France</li>
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<region>
<li>Grand Est</li>
<li>Lorraine (région)</li>
<li>Minas Gerais</li>
</region>
<settlement>
<li>Belo Horizonte</li>
<li>Metz</li>
<li>Nancy</li>
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<li>Université de Lorraine</li>
<li>Université fédérale du Minas Gerais</li>
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</region>
<name sortKey="Cerf, Loic" sort="Cerf, Loic" uniqKey="Cerf L" first="Loïc" last="Cerf">Loïc Cerf</name>
<name sortKey="Meira, Wagner" sort="Meira, Wagner" uniqKey="Meira W" first="Wagner" last="Meira">Wagner Meira</name>
<name sortKey="Silva, Arlei" sort="Silva, Arlei" uniqKey="Silva A" first="Arlei" last="Silva">Arlei Silva</name>
</country>
<country name="France">
<region name="Grand Est">
<name sortKey="Raissi, Chedy" sort="Raissi, Chedy" uniqKey="Raissi C" first="Chedy" last="Raïssi">Chedy Raïssi</name>
</region>
</country>
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