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Apr 03, 2024 185 likes •659 views

A Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs Daniel de Leng, Mattias Tiger, Mathias Almquist, Viktor Almquist, and Ni Nikla las Car arls lsson Linkping University, Sweden Proc. IEEE/IFIP TMA ,

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A Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs

Daniel de Leng, Mattias Tiger, Mathias Almquist, Viktor Almquist, and Ni Nikla las Car arls lsson Linköping University, Sweden

  • Proc. IEEE/IFIP TMA, Vienna, Austria, June 2018
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Motivation

  • Social media and micro-blogging service are becoming integral part in

many peoples lives

  • Many people use their mobile phone as a “second screen” during

games, TV shows, concerts, and other events

  • This allows users to easily interact with people far away, including (to

some extent) celebrities that they may not interact with otherwise

  • Many broadcasting companies, celebrities, and sports teams have

recognized this as a great opportunity to connect with viewers and fans

  • Researchers have only begun to analyze this trend and thus far most

second-screen studies have focused on TV shows

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Contributions at a glance

  • The first characterization of the second screen usage over the playoffs
  • f a major sports league
  • National Hockey League (NHL)
  • Stanley Cup playoffs
  • Both temporal and spatial analysis of the Twitter usage during the end
  • f the NHL regular season and the 2015 Stanley Cup playoffs
  • Analysis provides insights into the usage patterns over the full 72-day

period, with regards to in-game events such as goals, and with regards to geographic biases, for example, …

  • Quantifying these biases and the significance of specific events, we

identify important playoff dynamics impacting advertisers and third- party developers wanting to provide increased personalization

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Background, methodology, and dataset

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Introducing Lord Stanley, the oldest and “best” trophy in professional sport … (*)

… and my own journey to the cup …

Sources: https://www.foxsports.com/southwest/gallery/the-all-time-best-trophies-in-sports-062114 https://en.wikipedia.org/wiki/Stanley_Cup

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… true happiness during visit with the cup!

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… a second attempt …

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The big guys jo journey to the Cup

Source: The independent

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Data collection

  • Use Twitter Streaming API
  • Subscribe to tweets including certain hashtags/keywords
  • 1% “firehose” sometimes come into effect, but at those times we

know missed volume

  • Adapt the set of #hashtags we follow on a daily basis
  • Official hashtags for all NHL teams
  • Per-day specific tags based on today’s games
  • Update tags during low-activity hours (morning in America)
  • For set of example games, we also collect detailed per-minute

information about goals, etc.

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Second screen usage

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Mobile cli lients

  • Majority (88%) of these tweets are from mobile devices
  • With iPhone/iPad and Android leading the way ..
  • Together with high twitter activity at time of in-game events, this

supports that twitter is used as a second screen

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Mobile cli lients

  • Majority (88%) of these tweets are from mobile devices
  • With iPhone/iPad and Android leading the way ..
  • Together with high twitter activity at time of in-game events, this

supports that twitter is used as a second screen

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Skewed usage

  • Tweets per user follows power-law relationship
  • Clear linear relationship on log-log scale
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Lo Longitudinal usage and ty type of f tw tweets

  • Highest activity the last days of regular season and last day of playoffs
  • User engagement went down as teams were eliminated
  • Interest increased again for finals; six clear spikes (one for each game)
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Lo Longitudinal usage and ty type of f tw tweets

  • Highest activity the last days of regular season and last day of playoffs
  • User engagement went down as teams were eliminated
  • Interest increased again for finals; six clear spikes (one for each game)
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Lo Longitudinal usage and ty type of f tw tweets

  • Highest activity the last days of regular season and last day of playoffs
  • User engagement went down as teams were eliminated
  • Interest increased again for finals; six clear spikes (one for each game)
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Location of tweeters: Dis istance to clo losest arena

  • Most tweets from close to city with NHL team
  • E.g., 50% within 17.8 km and 90% within 324 km of closest arena
  • Most tweets not from arena itself
  • E.g., Less than 7.5% within 1km from arena
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Location of tweeters: Dis istance to clo losest arena

  • Most tweets from close to city with NHL team
  • E.g., 50% within 17.8 km and 90% within 324 km of closest arena
  • Most tweets not from arena itself
  • E.g., Less than 7.5% within 1km from arena
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Location of tweeters: Dis istance to clo losest arena

  • Most tweets from close to city with NHL team
  • E.g., 50% within 17.8 km and 90% within 324 km of closest arena
  • Most tweets not from arena itself
  • E.g., Less than 7.5% within 1km from arena
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Lo Location: Fading in interest aft fter eli limination

  • Highest interest in championship city (CHI)
  • Interest highest in cities with teams that went further
  • Peaks associated with Canadian playoff cities and traditional hockey

markets (e.g., NYR, MTL, MIN, OTT, NYI, TOR)

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Lo Location: Fading in interest aft fter eli limination

  • Highest interest in championship city (CHI)
  • Interest highest in cities with teams that went further
  • Peaks associated with Canadian playoff cities and traditional hockey

markets (e.g., NYR, MTL, MIN, OTT, NYI, TOR)

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Lo Location: Fading in interest aft fter eli limination

  • Highest interest in championship city (CHI)
  • Interest highest in cities with teams that went further
  • Peaks associated with Canadian playoff cities and traditional hockey

markets (e.g., NYR, MTL, MIN, OTT, NYI, TOR)

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Lo Location: Fading in interest aft fter eli limination

  • Highest interest in championship city (CHI)
  • Interest highest in cities with teams that went further
  • Peaks associated with Canadian playoff cities and traditional hockey

markets (e.g., NYR, MTL, MIN, OTT, NYI, TOR)

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Lo Location: Fading in interest aft fter eli limination

  • Highest interest in championship city (CHI)
  • Interest highest in cities with teams that went further
  • Peaks associated with Canadian playoff cities and traditional hockey

markets (e.g., NYR, MTL, MIN, OTT, NYI, TOR)

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Tweet volumes during each round

  • End of season proportional to number of teams in each category
  • Steady increase in interest for teams reaching final
  • Increased interest for participating teams of each round
  • Reduced interest among eliminated teams
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Tweet volumes during each round

  • End of season proportional to number of teams in each category
  • Steady increase in interest for teams reaching final
  • Increased interest for participating teams of each round
  • Reduced interest among eliminated teams
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Tweet volumes during each round

  • End of season proportional to number of teams in each category
  • Steady increase in interest for teams reaching final
  • Increased interest for participating teams of each round
  • Reduced interest among eliminated teams
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Tweet volumes during each round

  • End of season proportional to number of teams in each category
  • Steady increase in interest for teams reaching final
  • Increased interest for participating teams of each round
  • Reduced interest among eliminated teams
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Tweet volumes during each round

  • End of season proportional to number of teams in each category
  • Steady increase in interest for teams reaching final
  • Increased interest for participating teams of each round
  • Reduced interest among eliminated teams
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Tweet volumes during each round

  • End of season proportional to number of teams in each category
  • Steady increase in interest for teams reaching final
  • Increased interest for participating teams of each round
  • Reduced interest among eliminated teams
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Tweet volumes during each round

  • End of season proportional to number of teams in each category
  • Steady increase in interest for teams reaching final
  • Increased interest for participating teams of each round
  • Reduced interest among eliminated teams
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Tweet volumes during each round

  • End of season proportional to number of teams in each category
  • Steady increase in interest for teams reaching final
  • Increased interest for participating teams of each round
  • Reduced interest among eliminated teams
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Hashtag usage

  • Zipf-like popularity skew of hashtags
  • Most frequent hashtags associated with the same teams as

dominated the geo-based analysis ...

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Per-game analysis

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Tweet spikes during example game

  • Significant spikes when goals and at the end of the game
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Tweets per min inute during in in-game events

  • Significant spikes when goals and at the end of the game

Baseline

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Tweets per min inute during in in-game events

  • Significant spikes when goals and at the end of the game
  • Similar observations for other games
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In In-game lo location-based analysis

  • Majority of activity close to participating cities
  • E.g., 43-50% within 100km and 63% within 300km of arena of

participating teams

  • Spike in MTL-OTT game due to Toronto
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In In-game lo location-based analysis

  • Majority of activity close to participating cities
  • E.g., 43-50% within 100km and 63% within 300km of arena of

participating teams

  • Spike in MTL-OTT game due to Toronto
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In In-game lo location-based analysis

  • Majority of activity close to participating cities
  • E.g., 43-50% within 100km and 63% within 300km of arena of

participating teams

  • Spike in MTL-OTT game due to Toronto
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Tweets during example game: DET vs TBL

  • Another example …
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Tweets during example game: DET vs TBL

  • Another example …

Detroit (DET) Tampa (TBL) Toronto (TOR)

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Tweets during example game: DET vs TBL

  • Another example …
  • A closer look reveal huge imbalance in the location of tweets

associated with the two teams: TBL in Florida region, and DET in rest

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Conclusions

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Conclusions

  • We present the first characterization of the second screen usage

during individual games and across an entire playoff

  • Both temporal and spatial analysis of the Twitter usage during the

end of the NHL regular season and the 2015 Stanley Cup playoffs

  • Evidence that Twitter is used for real-time second screen usage
  • The majority of these tweets are done using mobile devices and

more new content is generated during games (e.g., spikes at time

  • f in-game events and lower retweet ratios)
  • Tweeting actively is heavy tailed, roughly half of the tweets are

retweets, and there are significant geographic biases

  • Our geo-based analysis shows that the majority of tweets are from

the regions closest to the competing cities, with a tail of tweeters further away, there is a high bias towards mentioning the local team, and user engagement drops significantly when local team eliminated

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Niklas Carlsson (niklas.carlsson@liu.se)

Thanks for listening!

A Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs

Daniel de Leng, Mattias Tiger, Mathias Almquist,

Viktor Almquist, and Niklas Carlsson

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