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Big Data thinks small

Updated: 2013-05-12 08:43
By Deng Zhangyu (China Daily)

Liu's company collects user data from Weibo, which had more than 500 million registered users by the end of 2012, Renren (China's answer to Facebook), Douban (a community-oriented social network) and search engines.

"We can identify individuals through social networks," Liu explains.

Big Data thinks small

"We can monitor what they post and discuss to predict what kinds of films will be popular during certain periods."

Liu and his team of 10 engineers collect and analyze data on every film's director, lead actors and actresses, fan loyalty and buzz about the film.

"We examine different dimensions - up to 100 - of every user, including time, location, semantics, circle of friends, etc."

Entdigital can now predict revenue for 70 percent of films in Chinese theaters with 85 percent accuracy, Liu says.

"I hope to give efficient guidance to film producers as early as possible this way," he says.

Producers buy the company's analyses to determine their marketing strategies.

While "Big Data" and "data crunchers" are buzzwords in China's dotcom sector, the country's industry is in its infancy.

"The core value big data brings is analytics through quantitative methods, but these methods were, to some degree, ignored in Chinese culture's long history," says Tu Zipei, director of Asia-Pacific Area at KIT Solutions and author of Big Data Revolution.

Because it's in the early stages, it's harder to trust China's data, says Frank Yu, who has worked in information technology for 20 years. The former Microsoft specialist and current CEO of the crowd-sourcing platform Kwestr points out the lack of data from previous years and murky transparency of public organizations makes this trickier.

There are also privacy concerns, which pose a problem in every country.

Tu explains: "Companies monitor consumers' behavior by various digital means for profit. Governments sit atop data mountains and play the role of Big Brother."

Liu says one could theoretically glean all information about an individual. But it would require a lot of money and manpower because the information is scattered among numerous terminals.

Companies are currently more interested in digging through masses of data from tens of millions of people, rather than any one of them.

Wang, who invests in 16 data analytics startups, expects this might change.

"Computers automatically process epic amounts of data. We can stamp individuals with a code of, say, 0001. But we only know what 0001 does and what we should recommend to him. It's beyond our capacity to know who he is."

What does this mean for privacy?

"The safest way to hide a leaf is to put it in a forest," Wang says.

 

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