|Year : 2021 | Volume
| Issue : 1 | Page : 62-65
An analysis on top commented posts in reddit social network about COVID-19
Khalil Kimiafar1, Mehdi Dadkhah2, Masoumeh Sarbaz1, Mohammad Mehraeen2
1 Department of Medical Records and Health Information Technology, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran
2 Department of Management, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
|Date of Submission||27-May-2020|
|Date of Decision||03-Aug-2020|
|Date of Acceptance||15-Aug-2020|
|Date of Web Publication||30-Jan-2021|
Department of Management, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Kimiafar K, Dadkhah M, Sarbaz M, Mehraeen M. An analysis on top commented posts in reddit social network about COVID-19. J Med Signals Sens 2021;11:62-5
|How to cite this URL:|
Kimiafar K, Dadkhah M, Sarbaz M, Mehraeen M. An analysis on top commented posts in reddit social network about COVID-19. J Med Signals Sens [serial online] 2021 [cited 2021 May 14];11:62-5. Available from: https://www.jmssjournal.net/text.asp?2021/11/1/62/308422
At the moment, people have been quarantined for COVID-19 management. In such a situation, people share their concerns, ideas, questions, etc., through social media more than before. Face-to-face relationships have been replaced with virtual relationships through the Internet. COVID-19 will not be controlled without people's collaboration with medical personnel, managers, and policy-makers (source: authors' observation). Besides working on the treatment of patients, researching to find the COVID-19 vaccine, etc. It is essential to consider people's concerns and try to address them for gaining more co-operation from their sides. In this regard, social media mining can help to understand what is on the point of discussion about COVID-19 by the public. By gaining a list of topics, we can plan better for dealing with COVID-19 as the public have a vital role in the prevention of virus dissemination.
For that purpose, we follow some sources and tutorials on social network mining and textual data analyzing.,,, Based on the mentioned sources, the methodology of our research is presented below. We selected Reddit as the social media for study. Based on Statista, Reddit is in the list of popular social networks globally and has about 430 million active users. Reddit visitors are mainly from the USA, UK, Canada, Australia, and Germany. Most of Reddit users are male and young. To understand what people say about COVID-19, we searched the terms “COVID-19” and “corona virus” in the title of Reddit's posts (search date was March 31, 2020). Then, the top commented posts for each searched keywords were extracted. The total number of extracted posts was about 460. This process was carried out semi-automatically by the R tool and its packages. Then, to understand what people said about COVID-19, we utilized topic modeling and the Latent Dirichlet Allocation (LDA) algorithm. LDA identify topics in the textual data and present a list of keywords for each topic. In our research, LDA detected topics in the posts in which authors had left more comments on them. It is necessary to state that before using LDA, we should clean and prepare the extracted data to make it suitable for LDA analysis (preprocessing technique such as stop words removing, stemming, punctuation removing, etc.).
Using the mentioned method, we presented the keywords related to each topic in [Figure 1] as the words cloud (WC). A total of 12 topics was identified in the data and shown as the WC.
WC (a) reflects COVID-19 in the USA and the effect of this virus on this country. People discussed the spread of COVID-19 in the USA and made decisions to confront and limit the burden of this virus. WC (b) shows discussions about the symptoms of COVID-19, the ways this virus spreads, and its confrontation methods. This topic highlights attraction to the information needs of public people. People share and discuss the symptoms of COVID-19 and want to understand whether they are infected or not. In such a condition, people need to have access to valid and fruitful information. This will also reduce unnecessary referrals to hospitals. In some countries, the Ministry of Health has developed mobile/web-based applications to check people health statuses by answering some self-assessment questions about COVID-19. WC (c) emerged due to discussions about quarantine in different states, provinces, cities, etc. This topic indicates the number of detected COVID-19 cases after the quarantine and its effect on the prevention of COVID-19. By considering this topic, we need to provide suitable plans for leisure, support, education, and persuasion to comply with quarantine conditions for the public. WC (d) is about the cancellation of universities and colleges due to COVID-19. Some people share posts that show which universities and colleges suspended their activity and note the date of ending this suspension. These may be critical concerns for students, lecturers, academic staff, etc. They must meet some deadlines for research works or passing courses. There is a need to identify the academic population's concern as a subset of the public and address their concerns. WC (e) presents topics about questioning and answering in the social media (Reddit) or projects which encourage people to collaborate with sharing computing resources (sharing their computers' central processing units and random access memorys to conduct computations related to COVID-19 researches faster than ever). In this regard, it is necessary to provide a list of confirmed physicians in the social media for people to ask their questions. It is essential to detect spammers or fake accounts to prevent fake news. Policy-makers and health managers should introduce valid accounts and webpages to people for receiving valid information and news. WC (f) contains topics related to the management of information, conduction of discussions, removal of possible fake posts, etc., in Reddit. Bloggers and social media users should take care of the information they receive from social media and check the source of information. In the case of fake information, they should report posts since some users new to social media may interpret any information as valid. WC (g) is about positive COVID-19 tests of famous people such as senators, players, gamers, etc. It also contains information about the cancellation of some meetings, as well as self-quarantine. People follow news related to celebrities or famous people in the COVID-19 days! WC (h) emerged due to discussions about the reported cases of COVID-19 and discussions about this virus, mainly in China. The public is interested in such statistics as they hope to come back to regular living days. Hopefully, there are online websites such as Worldometer (https://www.worldometers.info/coronavirus/), which reports COVID-19 cases for each country. WC (i) reflects that stay at home to be safe from COVID-19. This topic contains posts that discuss the cancelation of travel, works, etc., to stay at home for preventing the spread of COVID-19. However, they should be intensives and laws so that people respect self-quarantine. Based on the WC (j), the risk of COVID-19 is another discussed topic. Some believe that COVID-19 is more dangerous than influenza, and some discuss the economic devastation of COVID-19. The public has concerns about what will happen after COVID-19 harness. These concerns should be addressed so that people collaborate with harnessing COVID-19. WC (j and k) appeared due to the posts about COVID-19 in Dutch.
Jelodar et al. used Reddit and analyzed available comments in subreddits. Our findings are somewhat similar to their results. The difference is the source of data, we analyzed posts, but they focused on users' comments. We focused on top commented posts, but they considered all available comments in selected subreddits. Hence, our research finding can be considered as the subset of their finding, because we focused on the most discussed content, not all them. In the research by Stokes et al., they analyzed all available posts between March 3 and March 31, (94,467 posts) from r/Coronavirus threads. They also share similar results. There are other research on the COVID-19 comments and posts analysis in Reddit or other social media such as tweeter.,,,, An interesting point is here, many researchers used social media analyzing technique to understand COVID-19 in the perception of people. The difference between these works is in the number of posts/comments/tweets, search date, data selection strategy, or/and method. Ordun et al. presented a list of 14 papers that analyzed tweets to understand COVID-19. The usage of social media is popular to understand the perception of people.
By considering H1N1, the recent pandemic in the world, there are similarities and differences between COVID-19 and H1N1 in public concerns. By reviewing available researches,,, we understand that during the H1N1 pandemic, the public considered doing some activities (such as washing hands) or refraining some others (avoiding overseas travel, avoiding crowded places, not eating pork, etc.) to cope with H1N1. They also have concerns about H1N1 infections and symptoms. This is somewhat similar to what people shared in their posts in WC (a), (b), and (i) for COVID-19. However, it seems that the severity of actions for coping with COVID-19 is more intense than that for H1N1. Furthermore, the economic devastation of COVID-19 is more critical. The total infected countries are also more than H1N1.
| Conclusion|| |
This piece highlights the discussed topics in the top commented posts in Reddit by users. Based on the findings, it is essential to understand the public concerns and addressed them. Different researchers used Reddit or other available social media to provide analysis about what people shared. These studies used different strategy to find related content. We recommend policy-makers to use all them to gain more comprehensive picture about phenomenon.
The presented information is based on the text mining of Reddit's posts (as the source of data) besides authors' interpretations and recommendations for addressing related concerns. As mining textual data is a somewhat challenging task, there may be some tolerances in the result.
Used packages and tool:
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