ABC News’ Dr. Mishal Reja Misquotes Study, Says Opposite of Study to Advance Left-Wing Agenda
- ABC News’ Dr. Reja quotes one of the five authors of a study to directly contradict a central premise of the study, doesn’t explain that the study says otherwise
- Study clearly says there is no proven connection between Tweet hashtags and actual in-person violence, but Dr. Reja quotes a study author to say the exact opposite.
- Study has obvious methodological flaws, Reja gives unbalanced one-sided view validating the study and not identifying its many problems
OUR RATING: Journalistic Malpractice. Even Salon.com is ashamed.
Indicted Outlet: Dr. Mishal Reja | ABC News | Link | Archive | 3/18/21
When you read the mainstream news, you are getting propaganda. You are getting the opposite of the information relevant to the issues of the day, because the media only presents one side: the left-wing agenda. Even when they quote left-wing studies, they purposefully deceive in order to advance the partisan agenda.
This is why the trust in American media is lower than in anywhere else in the surveyed world. [1]
Not content to breathlessly report on a left-wing study, ABC News Doctor/Reporter Mishal Reja purposefully quotes one of the study’s five authors to say what the study explicitly says they did not survey: that hashtags somehow cause violence.
Major Violations:
- Opinion as Fact
- Lying
- Lying Headline
- Statistics Abuse
- Bad Sources
- Ignoring Primary Sources
Here’s the headline from Dr. Reja:
Trump’s ‘Chinese Virus’ tweet helped lead to rise in racist anti-Asian Twitter content: Study
What does the study actually say? Did he actually read it critically and correctly? Notably the article does not even link to the study or even the abstract of the study. When an article is about something that’s online and they don’t link to it, there’s usually a reason they are ignoring the primary sources.
As usual with left-wing baloney like this, it’s usually revealed pretty quickly in the comments section, which is why most left-wing outlets have completely done away with comments.
Here’s the first gem of a comment:
Mick Price Kajsa Williams • 2 months ago
You say this because of a story about a story that literally lies about the study it’s about. The hashtags it counted weren’t all racist and there’s no way to know if there was ANY correlation between racist hashtags and Trump’s rhertoric. The study liiterally conflated racism with condemning the people ACTUALLY at fault for the pandemic, the CCP. So who is it that doesn’t have a sense or responsibility.
Here is the study in question. [2] Here is the full study. [3]
Here is the article’s abstract:
Objectives. To examine the extent to which the phrases, “COVID-19” and “Chinese virus” were associated with anti-Asian sentiments.Methods. Data were collected from Twitter’s Application Programming Interface, which included the hashtags “#covid19” or “#chinesevirus.” We analyzed tweets from March 9 to 23, 2020, corresponding to the week before and the week after President Donald J. Trump’s tweet with the phrase, “Chinese Virus.” Our analysis focused on 1 273 141 hashtags.Results. One fifth (19.7%) of the 495 289 hashtags with #covid19 showed anti-Asian sentiment, compared with half (50.4%) of the 777 852 hashtags with #chinesevirus. When comparing the week before March 16, 2020, to the week after, there was a significantly greater increase in anti-Asian hashtags associated with #chinesevirus compared with #covid19 (P < .001).Conclusions. Our data provide new empirical evidence supporting recommendations to use the less-stigmatizing term “COVID-19,” instead of “Chinese virus.”
So, in a period of two weeks, they are tracking Twitter hashtags and determining whether or not they expressed “anti-Asian sentiment.” There are so many methodological problems with this it’s hard to know where to start. These kind of problems are often part of what we’re calling statistics abuse in stories like this. It’s starting to look like commenter Mick Price is correct in his summation of the study’s problems.
As seen in other left-wing ‘studies’ that attempt to conveniently validate left-wing memes, the coding into the original database of the offending tweets is likely one enormous source of erroneous data. Meaning that the people coding the Tweets are likely enormously over-including things as expressing ‘anti-Asian sentiment’ than not.
One threshold question: would frustration at the Chinese government count as ‘anti-Asian sentiment’? The answer is yes.
Here’s what the study said about how they coded the offending tweets:
To characterize anti-Asian expressions, the hashtags were independently coded by 2 trained research assistants who were blinded as to whether the hashtags belonged to #covid19 or #chinesevirus.17
The characterization of the hashtag was done through a qualitative investigation of the tweet and its neighboring hashtags. A hashtag was considered anti-Asian if it (1) was opposed to or hostile toward the region, the people, or culture of Asia; (2) demonstrated a general fear, mistrust, and hatred of Asian ethnic groups; (3) supported restrictions on Asian immigration; or (4) used derogatory language or condoned punishments toward Asian countries or their people. Examples of anti-Asian hashtags included #bateatingchinese, #yellowmanfever, #makethecommiechinesepay, #disgustingchinese, #commieflu, #chopstickchins, and #chinkflu.
So let me simplify that for you:
A hashtag was considered anti-Asian if it (4) used derogatory language or condoned punishments toward Asian countries or their people.
So tweeting:
Wow I wish the Chinese Government weren’t so corrupt. #chinavirus
Or
The Chinese Government is incredibly repressive and violates human rights, as seen in this latest crisis. #chinavirus
Or
Help me I’m a Uighur trapped in a concentration camp that my Chinese government slave masters and western media, including many media elites, won’t talk about for some reason! #chinavirus
All three were likely coded as ‘racist’ by these left-wing academics and shoved into their database so that they could score cheap political points because it 1) used the offending hashtag, and 2) used derogatory language, 3) toward an Asian country.
Here’s what Dr. Reja took away from this study:
A new study suggests that former President Donald Trump’s inflammatory rhetoric around the coronavirus, which is believed to have originated in China, helped spark anti-Asian Twitter content and “likely perpetuated racist attitudes.”
Here’s how he connects it to ‘hate crimes’
The results, published in the American Journal of Public Health, come in the wake of a string of attacks on Asian communities in the U.S., including a series of shootings in Georgia that left six women of Asian descent dead.
Even though, as we’ve pointed out ad nauseum here, the Atlanta spa shootings have zero evidence connecting them to a racial motive, and in fact several of the victims were not Asian. So this is another instance of creating false connections.
The actual study doesn’t even make a connection between hashtags and hate crimes, they just say it’s ‘implied.’ Here’s their exact language:
Although we were unable to assess the relationship between hateful hashtags and hate crimes, our results provide a plausible connection because many tweets and hashtags implied violence.
They even admit that it’s unlikely to be a direct cause in the study:
Furthermore, even if the probability of a hashtag leading to a hate crime is low, the large volume of new hashtags might translate to a noticeable increase in incidents. Indeed, even a single hate crime is 1 too many.
The words “might translate” and “a single hate crime is 1 too many” isn’t exactly, you know, hard science in the study world. It’s called “complete and total conjecture” and revealing this thing called “bias” and “prejudice” instead of “science.”
When there’s no connection demonstrated except for one that you hope for? Protip: not science.
This is their opinion as fact within the study. They could have written the study just to measure social discourse and perhaps the racializing of discourse, I don’t know, something that might be a little more serious and a little less histrionic, but of course that would have denied the opportunity for left-wing quacks like Dr. Reja from breathlessly saying that hashtags equal violence.
In his article, Dr. Reja quotes one of the study’s authors as saying hashtags equal violence:
Dr. John Brownstein, an ABC News Medical Unit contributor and author of the study, said that such online conversations can spark violent reactions.
“We often see that online conversations that contain messages of hate don’t stay online,” Brownstein said. “Oftentimes, the conversations that take place on social media results in real world consequences.”
Even though, as I have cited here, the study very explicitly says that there is no direct causal connection to violence that they studied.
Just to be clear, the study said:
“…we were unable to assess the relationship between hateful hashtags and hate crimes…”
And Dr. Reja is quoting one of the study’s author as saying in the study:
“…online conversations that contain messages of hate don’t stay online…”
It’s almost as though Dr. Reja hasn’t read, or hasn’t cared to read, the actual study.
And if he’s not reading the study, or quoting things in his story that are completely opposite of what the study says, then why include the medical title in his byline? If a Doctor just goes off his gut instinct to treat you and avoids his training, test results, and instruments, is that a good Doctor or is that medical malpractice?
Thankfully journalists aren’t professionals, so when we complain about journalistic malpractice we’re usually only referring to CNN. But if journalism had enforceable standards, Dr. Reja wouldn’t meet them on this, or many of his other articles.
Which again is a sign that he’s ABC’s token doctor, trotted out to confirm left-wing memes with his title and not with his reasoned analysis.
OUR RATING: Journalistic Malpractice. Even Salon.com is ashamed.
Bibliography:
2 ] https://pubmed.ncbi.nlm.nih.gov/33734838/
3 ] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034032/
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