Bethany Lacina attempts to scientifically prove that #TheFandomMenace is a bunch of hateful racist, sexist and/or misogynist harassers, in a Washington Post piece entitled, Who hates Star Wars for its newfound diversity? Here are the numbers. Of course it’s all pure flim-flam, but let’s have some fun with this anyway.
No. It hasn’t.
The first link you’re pointing to about unflattering representation of men, is an unresearched piece where they fail to realize that The De-Feminized Fan Edit was in fact edited by a feminist SJW who was satirizing what they thought MRAs wanted to see.
In the second link about pandering to diversity that you’re linking to, the author lists Lando Calrissian as one of his favorite characters. Those who stupidly let the past die may be unaware, but the lead character Lando Calrissian was played by an African American actor – 38 years ago. The Return of the Kings article criticizes prioritizing diversity over story and character, which the Sequel Trilogy clearly does.
“Leftist moralizing” is an oxymoron.
Translated into reality speak, what this says is that SJWs began ignorantly chanting incoherent nonsense about race and gender when the media failed to clamp down on criticism of the film.
A narrative that hinges on the opinion posted in a single tweet by an unverified Twitter user, and for which there is exactly zero concrete evidence, which you can read about here.
You can also read about the far more likely explanation, that KMT temporarily disabled her Instagram account in order to better comply with an NDA while in production for Episode IX. Because her account wasn’t deleted, and is in fact still there.
In August, Tran wrote in the New York Times that online commenters “seemed to confirm what growing up as a woman and a person of color already taught me: that I belonged in margins and spaces, valid only as a minor character in their lives and stories.”
In fact she doesn’t reference online commenters at all. Rather, what you’re referring to is the editor’s note, and the headline which the editor also likely wrote. Kelly Marie Tran herself said nothing whatsoever about her Instagram account in that NY Times article which makes the NDA theory even stronger, and you can read more about that here.
In my research, I have investigated this phenomenon on Twitter, where offensive language and hate speech have a modest but clear presence — not because of automated accounts (“bots”) but because of humans. People use degrading language more frequently when they talk about women and minorities and when they talk to female fans.
The problem with the concept of hate speech is who decides what hate speech is. When the left decides, then anything that they disagree with instantly becomes hate speech. Therefore the term hate speech is utterly meaningless. The same goes for the phrase “degrading language.” In fact the left leaning Pew Research Center conducted a study that demonstrated what thinking people already know; that leftists are far more intolerant online than normal people despite all of the moronic lip service they give to tolerance.
You did research? Hilarious!
I collected thousands of tweets from Star Wars fans and used computer algorithms to characterize fan conversations. With tools developed at Cornell University, I examined tweets for positive or negative attitudes, “offensive language’’ (profanity and belligerence), and “hate speech,’’ which includes ethnic, misogynistic, and homophobic slurs, as well as threats of violence. Cornell’s algorithm also classifies extreme slurs against political and ideological groups as hate speech.
And who decided who would determine what exactly “hate speech” and “offensive language” is? Why, the fine uneducated leftist morons at Cornell University, I’m sure. How very scientific of them to have people program the algorithms, who are less likely to know that the Earth revolves around the Sun, and more likely to believe that astrology is scientific. Good job.
I found that in a keyword search for “Star Wars” or “The Last Jedi” (including variants and abbreviations), about 6 percent of tweets used offensive language. I removed false positives in which the algorithm misunderstood the context. On the other hand, the algorithm cannot detect politely worded attacks, so it’s possible that it underestimates abuse. Nor could I count tweets deleted by their author or for violation of community standards, which disappear from Twitter’s archives. (Twitter’s data suggest about 5 percent of tweets are deleted.)
I don’t suppose you’d care to post the exact language of the specific tweets? You know, since snowflakes fall to pieces over just about anything these days? I mean, being offended is quickly becoming a vocation in and of itself.
Hate speech is rarer than offensive language, appearing in about one tweet out of 100. However, this is likely an underestimate of the amount of posted hate speech, since most hate speech is subject to deletion for violating community standards.
But how do you, or the fine folks at Cornell University, define hate speech?
Such tweets are not popular. Tweets with offensive language or hate speech are from accounts that have fewer followers than average. Further, these posts receive fewer endorsements (“likes” or “favorites”), retweets, or replies than more neutral posts.
So this is a popularity contest? Who was homecoming King and Queen?
Some observers have suggested that automated Twitter “bots” are responsible for anger or harassment in Star Wars Twitter. But I find no evidence for this. Using Botometer, a bot detector from the University of Indiana, I estimate that just 4.4 percent of Star Wars-related tweets are generated by bots. Tweets by bots contained offensive language less often than tweets by humans: 3 percent instead of 6 percent. Bots produced no hate speech tweets.
Oh, oh you poor, poor fool. You just violated one of the Collective’s primary narratives. they may come for you now.
I wanted to know how people tweet about Star Wars in general — and how that differs from how they tweet about women and minorities in Star Wars. I compared general Star Wars-related tweets to tweets about Kelly Marie Tran, the actress harassed on Instagram, or about Rose Tico, her “Last Jedi” character. The proportion of tweets with offensive language doubled from 6 to 12 percent — and hate speech jumped 60 percent, rising from 1.1 percent to 1.8 percent of all tweets.
But how is hate speech defined?
Not at all.
The algorithm measures abuse, not dislike. The difference in abusive language is even larger if we compare only negative posts. Fans complain about Star Wars’ first nonwhite female lead in more degrading language than they complain about other parts of the franchise.
But how do you define abusive language?
Tell that to Lucasfilm.
Twitter abuse is directed at female fans more often than male fans. To examine whether this was so, I collected and analyzed tweets sent to fan podcasts. I looked at 37 fan accounts run by men, and 26 by women. (Fans’ other identities, like race or sexuality, were mostly unclear.) The fan podcasters are not celebrities or Lucasfilm employees.
How do you define “Twitter abuse?” Have you thought of posting some examples?
Well at least Twitter abuse isn’t sexist.
Is it sexist to suggest that perhaps men just don’t get as upset over Twitter posts?
Offensive tweets and hate speech did not come only from those identified as politically right wing. Most posts are too generic to infer political views. But I did find that such belligerence also comes from the cultural left. Female podcasters, in particular, are attacked for not supporting diversity and gender equality strongly enough.
Most people who tweet about Star Wars are congenial and skeptical about “trolls.” But as with other cultural icons — whether it’s an all-female “Ghostbusters” or NFL players kneeling during the national anthem — a significant few respond with anger and hate when gender and race expectations change. We know that from the numbers.
Are you referring to the “Get Woke Go Broke” financials?
At any rate, for anyone who is interested, you can slog through the paper she wrote here.
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