Clarkson researchers publish study comparing disinformation about COVID-19 across languages, countries and platforms

A group of professors and student researchers at Clarkson University have published research aimed at assessing disinformation regarding COVID-19 in multiple languages, nations and social media platforms.

Golshan Madraki, assistant professor at the David D. Reh School of Business, said the group has been investigating disinformation and disinformation about COVID-19 on social media in multiple languages ​​and countries: Chinese (Mandarin) in China, English in the United States and Farsi (Persian) in Iran. The study spanned multiple platforms including Twitter, Facebook, Instagram, WhatsApp, Weibo, WeChat, and TikTok.

Madraki said the research took place while she, computer science professor Jeanna Matthews, and assistant professor of electrical and computer engineering Yu Liu were collaborating on other projects.

“It was in the middle of the pandemic and all of our meetings were zoomed in with no real social interaction. Therefore, during the first few minutes of our meetings, we would usually socialize and always end up talking about COVID and all the crazy nonsense we heard about COVID, ”she said. “We noticed that since each of us used different social media platforms (i.e. Yu mainly uses Weibo and WeChat in Chinese; Jeanna mainly uses Twitter and Facebook in English; and I mainly use WhatsApp, Telegram, Instagram, TikTok and Facebook in Farsi), we have been exposed to different types of disinformation that the other two haven’t even heard of. This actually prompted us to research the literature for differences in disinformation (especially related to COVID) on different social media platforms in different languages. “

The trio, along with graduate student Jacqueline Otala and undergraduate student Isabella Grasso, defined misinformation, misinformation, misinformation and “infodemic” during their research. Infodemic refers to the danger of misinformation during the pandemic.

The group explored why disinformation about the pandemic is so powerful, used sampling to record distinctive elements of debunked disinformation, and used a qualitative approach to categorize the topics and roots of disinformation across languages ​​and platforms of concentration.

According to Madraki, the group found that in all three countries, the source of the disinformation was the government or politicians. She also said that the English and Farsi disinformation samples have more in common in terms of the subject of disinformation than Chinese, especially when it comes to the actions of the individual. The different levels of government restriction on social media also have an influence.

Madraki said that while the Iranian government enforces certain restrictions, the influence of the Chinese government is harder and Iran has more access to free internet, which sometimes exposes them to English disinformation.

The lack of disinformation with criminal roots and fewer categories of disinformation overall in Chinese social media is notable and underscores the trade-off in controlling disinformation, Madraki added. A key challenge for the future, she said, will be figuring out how to control disinformation without silencing the voices needed to hold governments to account.

Madraki said it is sometimes difficult to detect misinformation from the facts, especially when the misinformation targets sensitive topics that could affect our judgment and sensitivity. She also offered some tips to make sure the information you read on social media is accurate.

“The next time you see content on your social media feeds that doesn’t match, please search about it,” Madraki said. “Fact-checking technologies have advanced since the start of the pandemic. For example, Google search and its fact-checking technology can go a long way in recognizing misinformation and factual disinformation.

The full study, titled “Characterizing and Comparing Disinformation on COVID-19 Across Languages, Countries and Platforms,” can be found at https://dl.acm.org/doi /pdf/10.1145/3442442.3452304.

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