Netizens love "net sun" physical conditions scientists want to use to track disease

A sentence or alertable epidemic on your social network

"Cold, do not want to cook ..."

In the event of a cold, many people would publish a status on Weibo or Renren to their friends and relatives. This was originally a very common thing. Recently, however, some scientists have suggested that we can use everybody's daily status updates and topic keywords on social networks to establish a frontier epidemic warning system. In other words, an information about disease that you post at random may be a clue for future scientists to follow the disease.

Analysis of "Influenza Index" by Search Volume

It is understood that in recent years, people have discovered that through social networks or search engines, traces of the spread of the flu can be found and traced. In February of this year, a professor at the Center for Disease and Prevention in Atlanta, USA, proposed that social networks could be used to track diseases.

With regard to this idea, you can search for a lot of past information. According to foreign media, from 2008 to 2009, Google and Yahoo have discovered that when the flu in a certain area begins to erupt, the number of keywords related to Internet search and flu will change, so the key to search engines Word analysis, such as "cough," "fever," and "pain," helped people find the path to the flu and effectively stop the spread of the flu. In 2010, Google launched the "Influenza Index" to provide flu prediction information for the general public.

For flu, traditional flu surveillance is very important, but most health agencies only focus on a single country or region. Google’s flu trends are being updated every day and can detect worldwide data and can be a useful supplement to the health care system. Allegedly, Google tested the tracking effect in nine regions of USA, and found that this system accurately predicted the outbreak of influenza 7 to 14 days earlier than the USA Federal Center for Disease Control, and it was during this time that the spread of the flu was controlled. The important period of time.

Recently, some scientists have also proposed to analyse data by analyzing information on diseases that users publish on social networks such as Weibo, so as to achieve the purpose of epidemic early warning.

Many people will go online and “hang” their physical condition

The Jinling Evening News reporter found in the survey that many people have the habit of “hanging” their physical condition on their own Weibo or Renren online. Entering the word "cold" on Weibo can find a lot of information about "cold". The netizen's "Jiao Lulu _cat" hangs out: "I have a cold, I don't want to cook ... I come to the porridge store with my dear to get rid of the fire porridge." Not only the status, but also the status of the release status "Weifang City, Shandong Province Weifang District, Xiangyang Road." Such precise content is very effective information for data analysis. The netizen Qiu Ting’s state of the red leaves said: “Good afternoon, catch a cold!” and forwarded the status to his circle of friends. He quickly got a friend’s response to comfort, and a friend responded and said, “My military training has returned with a cold. get up."

Reader Ni Ping told reporters that she likes to update her status on Weibo or everyone. Whether she is sick or buys new clothes, she is willing to share with others. "In the past, I modified my status on the QQ record. Now I have Weibo, and I'm updating it. Once I just sent Weibo and said, 'Finished,' and after two minutes, some of my classmates called and asked if I was doing something. !”

Insiders: The prerequisite is that participants are willing to share

So how can this kind of epidemic alert through social networks be feasible?

Dr. Cui Yijun, a doctoral student in the communication and information system at the School of Electronic Information Engineering of Nanjing University of Aeronautics and Astronautics, said that he personally thinks this is a very good application for social networking sites.

"Through some of the activities of each of us, on social networking sites, it is very meaningful to come up with some work that will help prevent the epidemic." However, Cui Yijun said that he thinks this method is only one of the conventional methods. It is not possible to completely replace the traditional epidemic prevention and early warning methods.

Cui Yijun said that the main reasons are the following two aspects: The prevalence of epidemics through social networks is predicated on the fact that each participant is willing to contribute and share this information. This involves key issues and is an issue of personal privacy.

Although some scholars say that statistics are not made on individuals, they do not represent that privacy has not been compromised. With small-scale statistics, users are more likely to share some information without knowing.

Once the commercialization of such information is used, the user may not be actively sharing as before when he or she may be searched and tracked in consideration of personal privacy.

Second, social networks such as people or Weibo can share a lot of information and bring positive value, such as the use of notifications, warnings, and other fields.

"But we can easily see that there are also some rumors, false advertising messages, etc. on social networks. If you use micro-blog and other social networks to establish epidemic early warning systems, how to deal with these non-real information, will be a difficult point." Cui Yijun said .

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Those related to "social networks"

Social networking has become an indispensable part of our lives. It allows us to instantly understand information, make like-minded friends, and express our own feelings. Social networks are changing our lives.

In a survey, 24% said they missed important private moments because they were busy sharing on social networks.

Every day, Facebook users around the world spend 10.5 billion minutes on the site, which is equivalent to 19963, and this does not include mobile users.

62% of people use social networks to share good news; 43% use social networks to share schedules with friends (overall rate is 16%); 84% use social networks to keep in touch with foreign friends.

Will social networks reduce our loneliness? In one survey, 39% of people spend more time on social networks than face-to-face; 20% prefer text messaging and online communication instead of the opposite; 33% prefer to chat with new online friends.

In a survey, when asked about the benefits of social networks, 25% said they could increase their confidence; 26% said they could promote new friendship; 83% said that they could help shame and lonely people make new friends. 76% said it helps to find old acquaintances.

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