ELECTRONIC SPORTS A new phenomena catalyzed by social TVs and a growing social community

Mehdi Kaytoue (INSA de Lyon/LIRIS) Loic Cerf, Wagner Meira Jr. (Universidade Federal de Minas Gerais) Chedy Raïssi - INRIA

Digitization of the society •  Services (the world of e-stuffs)

•  Information, news access •  Buying, booking •  Encyclopedia •  Social relationships/interactions •  Content access consumption (video, music, pictures) •  Many examples: forget about the “paper’’, consume digitized

Environment? Money! •  Access anywhere, anytime

•  Smart phones •  PC •  Tablets •  Extended TV services •  Consoles

Entertainment • Movies, music, sport, etc. content and main actors

followed on the Web

• Video games : A flourishing industry •  Assassin’s creed (2012): 40 millions euros budget, expected

revenue of 300 millions •  Angry birds: 600 millions of active players across the world •  Gaming communities appear •  Some games require skills to master at •  Competing spirit of (most of) games: one goal, to win •  As such, tournaments start to spread

Electronic sport •  10 years old in South Korea • Spreading to Americas & Europe strongly since 2010 • Organizations, league •  Teams composed of professional gamers, coaches • More and more championships • More and more software and hardware sponsor

to target an audience of 18-35’s males

Gamescom 2011, 2012: Dota competitions with $1 millions for the 5-players winning team

HuskyStarcraft Youtube channel, E-Sport commentator: 345 millions views,

685k subscribers

E-sport is professional

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What media to reach a growing audience?

Social TVs: Supply and Demand meet • A way for remote viewers (in space and time) to socially

interact about a video content •  Device/network (smartphones, pc, etc) •  Synchronization •  Modality (chat, voice) •  Social reach (family, friends, strangers)

•  Important upheaval of human interactions and socialization •  Watching TV tends to be more and more active •  (Crazy society!) Yahoo! and the Nielsen company:

86% of mobiles Internet users (and 92% of the 13-24’s) simultaneously watch TV and use the mobile phone

Following tournaments, leagues

Following gamers directly

Objectives • Assess, understand, characterize the phenomena through

its social Web community

• Evaluate, warn about its potential •  For industrials •  For researchers : a rich source of datasets, available (for now…)

M. Kaytoue, L. Cerf, W. Meira Jr., A. Silva, C. Raïssi. Watch me playing, I am a professional: a first

study on video game live streaming. Mining Social Networks Dynamics (MSND@WWW12).

M. Kaytoue, L. Cerf, W. Meira Jr. C Raïssi. Witnessing the digitization of sport through social TVs. (Submitted).

Data

Social TV: Entities of interest • Content/Object

Video content broadcast in live, also called (video) stream Surrounded with a chat tool

• Content producer Broadcasters, also denoted as streamers Produce the stream

• Content consumer Watchers, spectators, or viewers Consume the stream

•  Unregistered users: simply watch the stream •  Registered users: watch, chat, favorites, share

Dataset 1: Channels and their audience

An insight to video game channels, their activity, the topics that they cover, and their audience of any user (channel, date, audience, topic, category, description, …)

Dataset 2: Users IRC signals An insight to consumer activities, habits, behaviors of registered users

(user, channel, date, log in/out) (user, channel, date, message)

Dataset 3: Users favorite channels An insight into watchers interest outside the gaming world (user, channel, channel-category,channel-cumulated-audience, ...)

Characterization

Be serious, people really watch?

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Really, really? On a daily basis?

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Let me guess… who produce the content?

Typical Web content producers?

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Watching, a daily habit?

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What do they watch?

What do they watch?

Language, a frontier?

Channels Watchers

Language Proportion English 94.20 % Chinese 1.32 % French 0.85 % Japanese 0.72 % Telugu 0.71 % Portuguese 0.53 % Spanish 0.46 % Polish 0.28 % Russian 0.16 %

Language Proportion English 89.20 % French 3.28 % Chinese 2.34 % Spanish 1.40 % Japanese 0.93 % Telugu 0.47 % German 0.47 % Russian 0.47 % Polish 0.47 %

Who are they?

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animalsscience_tech

newssports

entertainmentsocial

gaming

Who are they?

What do they speak about?

Summing up briefly • E-Sport: an important phenomena at its start • Social TVs: wherenthe supply and the demand meet, dual catalyzers (Twitch.tv is an important E-Sport sponsor) • Addicts gather up around social TV to share/interact about

video games •  Young people (with their ‘’classical interests’’) •  Watching e-sport, question, enjoy/feel •  Discovering games before buying them •  Produced by USA (Europe follows) •  Daily activity/week-end activity •  Language barrier

Rich and accessible sources of data •  Twitch API • Prolific community on Twitter/Facebook • Specific game data

•  Official rankings •  Games logs •  …

• Many opportunities as application for your algorithms •  Graph mining •  Recommender systems •  …

• Understanding the data through a characterization allow to play the role of the expert in the application

Example of acquired chat session •  #steven_bonnell_ii> mutagling joins •  #steven_bonnell_ii> harvardmethaddict: AF server > EU •  #steven_bonnell_ii> juno1990ahn joins •  #steven_bonnell_ii> dadgun603 parts •  #steven_bonnell_ii> bennyschwein: i cant play while im

tired, maybe its the same here •  #steven_bonnell_ii> bobbyboosted: does minigun

stream? im new here i want to see him play •  #steven_bonnell_ii> ryunoske: Like, I won't be like "Idra

def didn't win" Because, Idra actually is really good. But... Idra def didn't win. D:

•  #steven_bonnell_ii> roamy01 parts

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Replays • A file storing all actions of a single game

•  Mouse click, selection, camera movement etc. •  Building/unit training, etc. •  Chat between players

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(Extremely!) Noisy Data • Actions are stored, but not their result • SC2 engine required to build the states: not available • Hard to evaluate states (current money, army, buildings)

• Mind game (use of fog of war and traps) • Mental & physical skills: vision/micro/macro

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A 1st experiment with replays • 18547 (unique) pro replays available at 30 Sept 2011. • Harvested from the 6 main online repositories • Sequence mining

•  determine frequent (surprising) (winning) strategies •  Only based on “build-orders”

• Several applications! •  Lot of information in replays (time, geo, selections, APM…)

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<(depot) (barracks) (refinery) …..> [WIN] <(hatchery) (spawning pool) (extractor) …..> [LOSS] …

Replay abstraction • Start from a huge noisy list of orders/events • Abstract it at different levels • Detect, name & interpret groups of events

(+ partOf relation => a lattice) • Helps in strategy characterization, event detection, data-

mining (e.g. replay clustering), AI design, player profiling, “turning point” detection, (supervised) Win ratio evaluation (like poker), etc.

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Ladder, Leagues & rankings

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Example of LiquiPedia information

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Social Sciences

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Artificial Intelligence

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Jusque dans les bars…

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