How social media analytics improves human well-being?

1.Can social media analytics be used to improve human well-being?

Yes. Nowadays, people have formed the habits of reading news on social media, such as Wechat, Twitter and Weibo. Since people can have easy access to Internet by using their smartphone, news spreads extremely rapid online. Besides, increasing number of people tend to post their health information or social event on social media. Intuitively, such information and its spreading on social media can be integrated into emergency surveillance, such like disease surveillance and infectious disease outbreak management.

Fig 1. (source: Google)

In 2015, researchers from Pacific Northwest National Laboratory [1] investigated such question and their studies showed that social media did play role in disease surveillance. Moreover, in their studies, they investigated more than 33 manuscripts and found that social media assisted disease surveillance and public health management covered many diseases, including Influenza-like Illnesses, Infectious Diseases, and even Medication and Vaccines.

Fig 2. (source: https://www.illumina.com/areas-of-interest/microbiology/infectious-disease-surveillance.html)

Some reader might cast doubt on such idea. “Why do we need it? Don’t we have experts in National Centers for Disease Control and Prevention (CDC)?” It is true that the CDC will post disease surveillance to the public as soon as they can. However, the CDC is somehow restricted by its time-consuming virological test results from laboratories and relatively large number of outpatient reporting. The CDC usually confirmed outbreaks within about 2 weeks after the disease began. In contrast, social media can report such emergency much faster.

2.How does social media analytics work for it?

In this paragraph, some examples of using social media analytics in disease surveillance and emergent events management will be displayed. Readers might learn from these examples and better understand how social media analytics be used to help human being.

Fig 3. (source: https://altarum.org/solution/disease-surveillance-and-data-quality)

In one study [2], researchers from University of Bristol discovered that health related words like “cough nigh”, “swine flu”, and “sore head” tracked with reported Influenza-like Illnesses outbreak in England. During that time, terms, including “influenza”, “symptom”, “infection” and “flu”, tracked users concerns. And they reported that data analysis on Twitter content could predict flu outbreak approximately one week ahead of CDC’s surveillance. Relevant studies were also reported by other researchers [3, 4].

Except disease surveillance, social media analysis supports government in decision-making. At the end of Jan on Wuhan city, the outbreak of novel coronavirus caused rapid consuming on medical supplies. One day, there came an emergent event that the majority of public hospitals in Wuhan City had lacked of medical supplies. The emergency spread extremely rapid on Weibo and Wechat. Since the “seeking for help” information consisted of doctors’ name and signatures, people immediately realized that it reported the truth, after simple data analysis. Partly benefited from social media analysis to identify the truth, the center government transported large amount of medical staff and all manners of medical supplies to Wuhan City.

Fig 4. (source: http://www.ce.cn/xwzx/gnsz/gdxw/202002/14/t20200214_34264833.shtml)

3.What should be minded?

However, social media is a double-edged sword; rumors can also be widely spread on it. Actually, a researcher from Medical College of Wisconsin once reported that “misleading posts were much more popular than the posts dispersing accurate, relevant public health information about the disease” [5]. When do social media analysis, people should be cautious about rumors and fake news.

References:

[1] https://www.ncbi.nlm.nih.gov/pubmed/26437454

[2] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3261963/

[3]https://www.researchgate.net/publication/256095323_Role_of_Social_Media_in_Early_Warning_of_Norovirus_Outbreaks_A_Longitudinal_Twitter-Based_Infoveillance

[4] https://link.springer.com/article/10.1007/s00779-015-0877-5

[5] https://www.ncbi.nlm.nih.gov/pubmed/27776823

How social media analytics improves human well-being?》有6个想法

  1. There is no doubt that the content of your article is very close to the latest hotspots and current events. It explains to readers the huge potential of social media analytics in promoting human well-being. Thank you for sharing!

  2. You think this example is very vivid and illustrates that social media has indeed affected human development and helped people to carry it out. The prevention and control of disease can also be used to soothe the heart. I think it is very valuable.

  3. Both of us are writing about the contribution that SMA could make to disease control and I think your blog is given much more details and examples. As you said in the first part, the traditional disease surveillance under the organizations like CDC would much slower and even reported after the disease outbreak. With the help of SMA, faster and more accurate measures could be made and drive to a better situation. I agree the part you mentioned about the rumors. In such urgent moment for China, it’s really important to distinguish the rumors and truth. Hope you can visit my blog if you have time, and we can further discuss this topic.

  4. Your blog is well-structured and you vividly discuss three main questions regarding your topic. I have two questions after reading this article. Firstly, you have mentioned that “Twitter content could predict flu outbreak approximately one week ahead of CDC’s surveillance”, but I wonder if there is any difference between the accuracy in predictions down by them. Secondly, since you said “misleading posts were much more popular”, how can we get rid of this kind of post when we do SMA? Hoping to discuss these question further with you!

  5. This blog is logistic. Social network combined with computer science could be applied to many field to solve different problems. Although each field has its own expert, they may need the help of social network to collect data and analyze the problem.

  6. You have a point. Due to various concerns, it may not be possible to report the outbreak at the first time. But through social media analysis, it can warn in advance

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