Google China Launches Earthquake Disaster People Search

Google China announced their launch of Google China People Search in the Google China blog to help victims and their relatives get in touch with each other. I have chosen to translate the announcement in full, and have included the original hyperlinks in the story.

Aside from the human tragedy, this is an excellent study in how Chinese Internet users turn to the BBS (all of the links except for the disaster area search platform below are to BBSes) during times of emergency.

As of this morning (May 16), there are 19,579 casualties, and total fatalities are estimated to total more than 50,000. Many families are continuously looking for their loved ones, in the hope that they will be able to find them safe.

Google China’s engineers, after working more than 24 hours, have created the disaster area search platform. We have attempted to gather information from across the Internet to make it easier for users to get information. Our objective is to create a platform where bravery and hope can meet.

We hope that your loved ones are not among the long list of fatalities. Maybe they are searching for victims in ruined buildings, maybe they are caring for the injured in a hospital, maybe they are feeding a child somewhere. Maybe they will hear our call and know that they are not alone in this disaster.

If you have any information about people you know who are involved in this disaster, please post their information to Tianya Laiba, Baidu Tieba, Soso Search, Sina, and Netease. You can also send email to us. Our engineers are at work 24 hours and we will regularly update our information.

Google’s influence in China is small, so we have made this code available to everyone. Any blog and website can include this code in their website so that more people and websites can join in this search.

This is a long recovery process and there is much more work to be done. May heaven protect China, and we hope that your loved ones will be safe.


寻找灾区的亲人

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Visualizing the Internet and Online User Behavior

One the things which has been interesting to me are visual maps of the Internet, which show the main websites, and usually, how much traffic they attract. One of the leaders in measuring Internet usage all over the world, and in Asia-Pacific, is Comscore, which recently prepared a report on Asia-Pacific Internet usage.

Today, we are swamped with data and different sets of variables, so much so that most executives prefer to have their data presented in some graphic form. One great pioneer in this field is Edward R. Tufte, whose book The Visual Display of Quantitative Information is considered a classic for all communicators who need to provide snapshots of large data sets in a simple and clear fashion so that business decisions can be made quickly and efficiently.

iA Japan has recently released a map of the Internet presented as a variation of the Tokyo subway map. Broadly speaking, larger sites are larger, while sites with less traffic are smaller.

Internet Web Trend Map

Now, I find myself spending more time thinking about how to visualize human behavior. Advertising and marketing have everything to do with understanding group behavior and psychology. While there have been books written about it, there has been almost no research done about how to visualize it. I find myself most interested in how groups of people move from one interest and website/s to another.

In the map, for example, I can see that among Chinese sites, Sina, Sohu, Netease and QQ are big, but I don’t know how people move to and from these sites, and to other sites. Static maps are about nouns; I’m also interested in the verbs and the adverbs. And not on a static basis as a snapshot, but in a live, ongoing, continuously evolving and changing basis in real-time.

How would online user behavior be visualized? One thing for sure: no static image would capture it; it would have to be like a video, constantly updated in real-time. And what insights would it give to marketers, advertisers, psychologists, anthropologists and linguists? My guess is that it would show that online user group behavior really has a lot in common with members of the animal kingdom which travel together in large groups, such as fish and starlings.

How about you? How do you think this data should be represented?

Since Google just announced a new university search API for research, maybe this could be a project it could be applied to.

Flock of starlings

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