This summer, the social media sphere will be buzzing again with fans and athletes posting about the 2016 Summer Olympics in Rio de Janeiro, Brazil. It will be the first Olympic games to take place in South America. You can also expect networks, publishers, and brands to get in on the social media experience by generating more content than ever before.
Looking back to the London games in 2012, just the social media interactions on Twitter alone were vast in terms of engagement:
– On Twitter, there were 960K mentions for Bolt, 830K for Phelps, and 490K for Tom Daley (British diver who took the bronze) during the games.
– The first day of Olympics, there were 3 million tweets in total.
The numbers go on and on, especially when you take into account all the views, likes, tweets by sports teams, athletes, and brands. There are plenty of useful stats out there from archives of the first ever “Social Games” as most tech blogs described it.
The Home Country Effect
In his home country, Tom Daly had social media buzzing more than Lebron and Kobe combined (138K and 134K tweets respectively per the same source). The Brazilian soccer team alone is likely to surpass all those stats combined. Football is the country’s national past time, and locals call their country “o País do Futebol”, which translates into “the country of football”.
Beyond the sheer increase in volume on social media in comparison to the 2012 London Olympics, the key significance of the 2016 Olympics will be the fact that a major portions of the content generated will be in Portuguese. Rio will have more users, more apps, and more channels than ever and it will have more diversity in languages, as well.
Perishable insights from real time analysis of all this multilingual content can easily turn into long term value for brands and businesses. Rio 2016 is precisely the type of event where Cross Language Information Retrieval and Analytics will be key capability for all the generated content.
Following the advances in Machine Translation (MT) technologies, the capabilities in Cross Language Information Retrieval became more available and effective than ever before. The combination of MT technologies with Natural Language Processing (NLP), Text and data mining (TDM) can gain new dimensions of insight. The process of understanding and driving value out of content should be equally effective when the languages change and multiply.
New Breed of Technologies
There are a number of newly emerging products and tools to prepare for the biggest social games yet. From customer service translate bots to multilingual sentiment analytics, there are simply more available language based options and tools to build or manage a brand or a product. Using API marketplaces, whether it’s a brand platform or a mixed ecosystem, product owners have a vastly increased amount of available resources to keep up with the new ideas.
SYSTRAN.io is a new cloud based platform for Natural Language Processing and Machine Translation technologies with APIs, microservices, and development tools. For partnership opportunities, please contact Craig.Stern@systrangroup.com.