From a player’s outlook and confidence level, to crowd support and the mood of the news, emotion just might be the most significant factor influencing the outcome of a tennis match. That’s why we gave US Open fans a new way to look at this game of emotion with IBM Watson’s help.
Throughout the tournament, we used IBM Watson cognitive APIs to reveal the emotions behind the game in real time: the Tone Analyzer API to uncover fan sentiment from social data; the Personality Insights API for player and fan personality profiles; plus the Alchemy News API to discover the current mood of the sports news. With Watson’s results, we created bespoke animations in real time and posted them on usopen.org/ibm for stat-hungry fans.
Fans could also discover their US Open Alter Ego by inputting their Twitter handle for Watson to 1) analyze their feeds to determine their personality profile, then 2) compare it to player profiles to determine which one is most like them. All in real time.
FP Print
All content we posted over the 14-day tournament could be shared on Facebook, Twitter and LinkedIn:
Insights
With IBM tournament data, as well as historical data, we were able to pull this and other insights for tennis fans.
Scores
Animations featuring scores were created from data gathered from match play and the IBM Data Center.
Social Momentum
Throughout the tournament, IBM Watson scoured popular hashtags relating to the tournament, then analyzed the data to give us current fan sentiment ratings.
News Mood
To get the mood of the sports news each day, we used Watson’s Alchemy News and Tone Analyzer APIs to analyze the sports headlines relating to the US Open around the globe.
Personality Profiles
Watson analyzed fans Twitter feeds to create their unique personality profile.
US Open Alter Egos
Watson compared fan personality profiles to player profiles to reveal fans’ US Open Alter Ego.