TY - GEN
T1 - Modeling and analyzing the video game live-streaming community
AU - Nascimento, Gustavo
AU - Ribeiro, Manoel
AU - Cerf, Loiclcerf
AU - Cesario, Natalia
AU - Kaytoue, Mehdi
AU - Raissi, Chedy
AU - Vasconcelos, Thiago
AU - Meira, Wagner
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/30
Y1 - 2014/12/30
N2 - In parallel to the exponential growth of the gaming industry, video game live-streaming is rising as a major form of online entertainment. Gathering a heterogeneous community, the popularity of this new media led to the creation of web services just for streaming video games, such as Twitch. TV. In this paper, we propose a model to characterize how streamers and spectators behave, based on their possible actions in Twitch and, using it, we perform a case study on the Star craft II streamers and spectators. In the case study we analyze a large amount of data collected in Twitch. TV's chat in order to better understand how streamers behave, and how this new form of online entertainment is different from previous ones. Based on this analysis, we were able to better understand channel switching, channel surfing, and to create a model for predicting the number of chat messages based on the number of spectators. We were also able to describe behavioral patterns, such as the mass evasion of spectators before the end of a streaming section in a channel.
AB - In parallel to the exponential growth of the gaming industry, video game live-streaming is rising as a major form of online entertainment. Gathering a heterogeneous community, the popularity of this new media led to the creation of web services just for streaming video games, such as Twitch. TV. In this paper, we propose a model to characterize how streamers and spectators behave, based on their possible actions in Twitch and, using it, we perform a case study on the Star craft II streamers and spectators. In the case study we analyze a large amount of data collected in Twitch. TV's chat in order to better understand how streamers behave, and how this new form of online entertainment is different from previous ones. Based on this analysis, we were able to better understand channel switching, channel surfing, and to create a model for predicting the number of chat messages based on the number of spectators. We were also able to describe behavioral patterns, such as the mass evasion of spectators before the end of a streaming section in a channel.
KW - starcraft
KW - streaming
KW - Tv
KW - twitch
KW - video game
UR - https://www.scopus.com/pages/publications/84921748877
UR - https://www.scopus.com/inward/citedby.url?scp=84921748877&partnerID=8YFLogxK
U2 - 10.1109/LAWeb.2014.9
DO - 10.1109/LAWeb.2014.9
M3 - Conference contribution
AN - SCOPUS:84921748877
T3 - Proceedings - 9th Latin American Web Congress, LA-WEB 2014
SP - 1
EP - 9
BT - Proceedings - 9th Latin American Web Congress, LA-WEB 2014
A2 - Almeida, Jussara M.
A2 - Pereira, Alvaro R.
A2 - Baeza-Yates, Ricardo
A2 - Baeza-Yates, Ricardo
A2 - Benevenuto, Fabricio
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th Latin American Web Congress, LA-WEB 2014
Y2 - 22 October 2014 through 24 October 2014
ER -