Presentation Title

Pandemic Related Fake News Identification Based on Unstructured Data Mining

Presenter Information

Fangyao LiuFollow

Advisor Information

Dr.Yong Shi

Presentation Type

Poster

Start Date

26-3-2021 12:00 AM

End Date

26-3-2021 12:00 AM

Abstract

The COVID-19, which is also called “Coronavirus” is keeping spreading worldwide at this moment. 62 countries have reported almost millions of coronavirus infections. Due to its contagious and zoonotic features, it has already caused many illnesses and death. The Center for Disease and Prevention (CDC), World Health Organization (WHO) and other media play a central role in broadcasting and updating news and prevention guidelines. All the information can keep all the people nationwide on the same page. However, a lot of fake news related to COVID-19 is harming our communities. The fake news creates challenges for governance. The fakes news offers some misleading information, which could be very dangerous. For example, one of the fake news said CDC officer suggests people stock up enough food and water as soon as possible. This fake news misleads many people who ran to the local grocery store, purchase many things that they may not need. This research project is going to using unstructured data mining methodology to identify fake news related to the ongoing pandemic (COVID-19). This project is very inspiring and creative. It can help us identify fake news immediately. Theoretically, this project contributes to future literature resources. Because it proposes a new fake news identification method, which specifically for the pandemic news. Technically, this project gives us a new idea about dealing with unstructured data.

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Mar 26th, 12:00 AM Mar 26th, 12:00 AM

Pandemic Related Fake News Identification Based on Unstructured Data Mining

The COVID-19, which is also called “Coronavirus” is keeping spreading worldwide at this moment. 62 countries have reported almost millions of coronavirus infections. Due to its contagious and zoonotic features, it has already caused many illnesses and death. The Center for Disease and Prevention (CDC), World Health Organization (WHO) and other media play a central role in broadcasting and updating news and prevention guidelines. All the information can keep all the people nationwide on the same page. However, a lot of fake news related to COVID-19 is harming our communities. The fake news creates challenges for governance. The fakes news offers some misleading information, which could be very dangerous. For example, one of the fake news said CDC officer suggests people stock up enough food and water as soon as possible. This fake news misleads many people who ran to the local grocery store, purchase many things that they may not need. This research project is going to using unstructured data mining methodology to identify fake news related to the ongoing pandemic (COVID-19). This project is very inspiring and creative. It can help us identify fake news immediately. Theoretically, this project contributes to future literature resources. Because it proposes a new fake news identification method, which specifically for the pandemic news. Technically, this project gives us a new idea about dealing with unstructured data.