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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 Niklas Carlsson Linköping University, Sweden Proc. IEEE/IFIP TMA, Vienna, Austria, June 2018

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Page 1: A Second Screen Journey to the Cup: Twitter Dynamics ...nikca89/papers/tma18.slides.pdf · A Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs Daniel

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

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 of a major sports league

• National Hockey League (NHL)

• Stanley Cup playoffs

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

• 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 clients

• 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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Longitudinal usage and type of 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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Longitudinal usage and type of 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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Longitudinal usage and type of 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: Distance to closest 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: Distance to closest 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: Distance to closest 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: Fading interest after elimination

• 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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Location: Fading interest after elimination

• 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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Location: Fading interest after elimination

• 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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Location: Fading interest after elimination

• 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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Location: Fading interest after elimination

• 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

Page 32: A Second Screen Journey to the Cup: Twitter Dynamics ...nikca89/papers/tma18.slides.pdf · A Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs Daniel

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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 minute during in-game events

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

Baseline

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Tweets per minute during in-game events

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

• Similar observations for other games

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In-game 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-game 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-game 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 of 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 ([email protected])

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

46