When the World Cup hits big data analytics IBM Social Big Data analysis

[Tenkine server channel] Brazil's World Cup craze has receded, this four-year football feast, in addition to staying up every night to see the sweat on the pitch of the players, but also to see a lot of High-tech technology, in such a data explosion in the era, based on large data analysis technology involved in sports industry is not surprising. Whether it is the performance of athletes on the court, the tactics of the coaches, the enforcement of the referee, or the experience of the outdoor fans, large data plays an important role.

This World Cup, you can see Google, Baidu, Microsoft and other giants through large data analysis of the results, so that the lottery "happy" A, Germany won the title behind the Matchinsight system, let the opponents lost a bit, and let the author's impression is more profound is the World Cup, large data and media collision.

Viewing social data from Tencent's World Cup report

The integration of large data analysis technology to media coverage is not new, in the beginning of the year, CCTV and Baidu Cooperation reported the "Spring Festival", the data news in a brand-new form to reflect. In this World Cup, Tencent Sports together with IBM application of large data analysis technology to make the report form and content are more unique than before. Apart from the topics of "scoring", "referee" and "unpopular", what are the fans concerned about? Social media let the earthly male and female fans have sold Meng Belly black gathering place. During the World Cup, in social media, QI and jokes, according to statistics, in the World Cup nearly half of the time, micro-blog on the World Cup discussion volume has been close to 1 billion times.

Once upon a time, in the track of media development, there is a key indicator is the efficiency and accuracy of transmission. In the era of information explosion, a report is no longer only depends on efficiency and accuracy, but can understand more users: what users care about, what to do, like to see what content, as well as the user orientation behind.

Taking the report of Tencent Sports to the 2014 World Cup as an example, unlike previous sports reporting patterns, Tencent used IBM's social data analysis and cloud computing technology to analyze the World Cup's extensive comments, views and voices on social networks, and to gain a focus on the fans. , the fans ' character, the fans ' view, so that we can see the different "Football report" and "grounding gas".

The relevant project leader was introduced in an interview with Tenkine, IBM and Tencent's cooperation is to all Chinese fans in public opinion, social tools in the "Voice" of the summary analysis, to get real-time hot spots, to provide Tencent, Tencent's editors and reporters as their own reporting a new source of information and topics.

In the form of these reports, the author highlights the "Fan Portrait", using IBM Social data analysis and a personal personality analysis model, the typical fans of different stars can be clearly sketched out to form fans portrait. For example, like Lionel Messi's character is characterized by "sensitive, glass Heart, organized", belong to the otaku female-style, Neymar fans of the key words for "simple, lively, love lively" and so on.

In an interview, Dr. Su, of the IBM China Research Institute, said the personality analysis model was based on cognitive psychology. Similar to psychological testing, the difference is that the previous psychological test method is to need an interview questionnaire, to many scenes, through the communication and psychological experts to judge the character. The IBM Institute did the research and compared the psychological test results with his social analysis data and found that there was a connection. This is why in the analysis of sports events, fans do analysis of the reasons. The so-called fan analysis, to Ronaldo as an example, in social media to the Ronaldo fans screened out, and football-related, and football unrelated to grasp down, so that the fans can analyze the typical character characteristics.

At the same time, the presentation and statistics of the support rate are different from the traditional, traditional research based on sample data, and through the IBM Semantic Analysis technology, the system can analyze the mass of fans on social networks, determine the attitude of different teams and stars, show real-time support rate.

This application of the technology is more complex, said in the middle, the first to carry out the substantive analysis, the collection of personal participation in the discussion topics included in the team, players and other elements, and then to carry out deep emotional excavation, that is, support or opposition to the judgment. "Many times we do some technology that actually wants to really make the computer understand human language, understand human behavior, and find bright spots and insights from behind." "The biggest feature of the IBM Social Data Analysis system is the use of a lot of machine-learning methods and natural language analysis techniques," said the Soviet Union. For example, the current system of deep emotional digging not only knows whether he likes it, but also knows why he likes it. At the same time, the system can really be like a person to understand some of the clues mentioned in an article, time, place people events, its vague language has 90% of the correct ability to judge.

Social relationships have been viewed as information in the past, but rarely defined as data, in foreign countries, Facebook, Twitter tried to make social information data, in the domestic, the application of this is rarely seen, Tencent and IBM This cooperation, let us see a good start.

Figure: IBM Social Data Analysis solution provides enterprise support for customer lifecycle in a social environment

Guo Shuyong, senior manager of Global Consulting services, IBM Greater China, said in addition to the media industry, IBM social large data solutions in the fast-sales, transportation and other industries have a lot of applications, can help enterprises understand customers, understand consumers, from the collection of information, through social and large data analysis methods, In order to help enterprises to develop precision marketing strategy, so as to achieve customer growth and trust.

Cloud computing behind Big Data

Large data processing is often inseparable from the cloud computing, in this cooperation between Tencent and IBM, the author mentioned above the semantic analysis, social large-scale solution, the support behind it also needs cloud computing to solve the problem of computational elasticity.

Not long ago, SoftLayer was introduced to the famous Watson, in which the social-data solution was deployed in a cloud-computing platform set up by SoftLayer in Hong Kong, and the results were immediately pushed to Tencent's World Cup website. In addition, the system will also share the results of the analysis to Tencent's editorial staff, to achieve real-time topic control.

Figure: SoftLayer Fully integrated solution

According to IBM GTS Cloud Services business Director Yu Zhongning, the World Cup cooperation in the number of visits is usually small traffic can not be compared to, for example, the 4 o'clock in the morning game found something need to expand, the system will automatically respond, quickly deploy these resources, only in order to meet the requirements of real-time. The value of cloud computing is this: you can react quickly when you need some resources, and SoftLayer has the characteristics of the public cloud itself.

Written in the last

Big Data:a Revolution that'll Transform how We Live, Work, and

People have been trying to find out how to get a better understanding of the world, from traditional statistics to large data analysis operations, before a considerable period of time in the concept, but very little can be truly integrated into the business, life and even the way of thinking. In essence, the media exists to solve the asymmetry of information. However, as a media worker, I often encounter some dilemma, we carefully produced the topic of the user side reflects flat, in fact, rely solely on the editorial experience of the judge to insight into the needs of readers is a problem. In this article, the Big Data analysis tool replaces the so-called experience and pulls the distance between the media and the reader. Sack, in other industries, large data analysis is subtly changing the rules of the game.