Blog (Medium.com)

(Please click the title to read the original articles on Medium.com)

July 12, 2020

Am I safe from COVID-19?

When I heard about COVID-19 for the first time I was in South Korea preparing for the next spring semester. I didn’t take it seriously; it seemed to be far from my concern. And then suddenly, WHO declared the coronavirus outbreak a pandemic. Things changed when Daegu, in South Korea, was host to the first large coronavirus outbreak outside of China, and borders between countries started to close. (Continued)

July 1, 2020

Risk Communication in Asian Countries: COVID-19 Discourse on Twitter

The novel coronavirus pandemic (COVID-19) has affected global health and the economy, and it has become a crucial topic on online platforms. The public discourse logged on online platforms helps us understand the concerns, risks, and strategies of people coping with the virus. When it comes to the quality of information, there have been numerous reports on the spread of misinformation (i.e., wrong by mistake) as well as disinformation (i.e., deliberately false). The abundance of such misleading content can be overwhelming to individuals in determining what information and guidelines to follow. The WHO has even called this phenomenon infodemic. 
(Reference: Coronavirus Disease 2019 (COVID-19) Situation Report) (Continued)

  • Authors: 
    Sungkyu Shaun Park, Sungwon Han, Jeongwook Kim, Meeyoung Cha (Institute for Basic Science & KAIST),
    Mir Majid Molaie, Jiyoung Han, Wonjae Lee (KAIST),
    Hoang Dieu Vu (HUST, Vietnam),
    Karandeep Singh (Institute for Basic Science)

June 9, 2020

Oddly humorous COVID-19 rumors: Gaining perspective on the fight against the infodemic

In early April, multiple 5G cell towers in the UK were set ablaze due to conspiracies claiming that they could spread a new virus. Dozens more arson attacks occurred in the following months. But what kind of vulnerability could cyber security specialists have found to warrant arsonists burning down telecommunication towers? Absurdly, the rumored 5G-transmissible virus was claimed not to be a software virus, but a biological virus, i.e. the novel coronavirus! This is only one of many fascinating rumors which have emerged all over the world during the ongoing COVID-19 pandemic. Get ready to scratch your head in bewilderment or chuckle at the oddities of pandemic rumors. (Continued)

  • Authors:
    Tung-Duong Mai, Sun Geng, Christopher B. Mokone, Meeyoung Cha (Institute for Basic Science & KAIST)
    Karandeep Singh, Richard Moore, Sung Jun Park (Institute for Basic Science)

May 15, 2020

Open data and COVID-19: Language diversity on Wikipedia

During the COVID-19 pandemic, people from around the world continue to turn to Wikipedia for vital information about the public health crisis. To meet this demand, Wikipedia volunteers have contributed over hundreds of thousand of edits dedicated to explaining the novel coronavirus, tracking regional cases, linking people involved, as well as discussing the socio-economic impact. Our three-part blog series analyzes the readership trends and insights that might help us understand how Wikipedia readers navigate through the wealth of COVID-related information on the site. (Continued)

  • Authors: 
    Changwook Jung, Sun Geng, Meeyoung Cha (Institute for Basic Science & KAIST), 
    Inho Hong (Center for Humans & Machines, Max Planck Institute for Human Development, Germany), 
    Diego Saez-Trumper (Wikimedia Foundation).

April 6, 2020

Open data and COVID-19: Wikipedia as an informational resource during the pandemic

From the very start of COVID-19, when it was known just as an outbreak of atypical pneumonia in China, people around the world have been finding and sharing information about the virus on Wikipedia, a frequent online resource for medical information. While the content and quality of the information on Wikipedia is shaped by volunteer editors (over 34K contributing to COVID-19 related pages) and by policies about verifiability, the activity generated by these volunteers and readers also generates a considerable amount of data itself. For example, we can explore how many Wikipedia articles have been created about COVID-19 related topics. Which sources are cited in those articles? How many people had reviewed such articles? Which are the most visited pages? (Continued)

  • Authors:
    Changwook Jung, Sun Geng, Meeyoung Cha (Institute for Basic Science & KAIST),
    Inho Hong (Center for Humans & Machines, Max Planck Institute for Human Development, Germany),
    Diego Saez-Trumper (Wikimedia Foundation).