The Elon Musk Twitter shitshow
- Thread starter CleteyColgate
- Start date
You mean the thousands of accounts with 3 followers and a hottie in the picture talking about how it was Mayor Pete’s fault weren’t legit?
Next you’re gonna tell me people retweeting Tucker Carlson don’t have America’s best interests at heart.
How Sprinklr Helps Identify and Measure Toxic Content with AI
New AI Model can analyze publicly available digital data to detect the presence of toxicity and provide context on the scope and impact of toxic content.
www.sprinklr.com
How Sprinklr Helps Identify and Measure Toxic Content with AI
“New AI Model can analyze publicly available digital data to detect the presence of toxicity and provide context on the scope and impact of toxic content.
The challenges brands face to capture and analyze online conversations, and advertise alongside them, have continued to accelerate. The sheer volume of conversation on social and digital platforms is a daunting barrier to entry for many. Toxicity on social media – rhetoric motivated by hatred, prejudice or intolerance – is unfortunately another persistent reality and growing concern for brands, especially as it relates to “brand safety”.
Brand safety refers to how well a brand is protected from being associated with inappropriate or offensive content. Offline, brand safety concerns are why advertisers may drop celebrity endorsements due to personal behavior or controversy. Online, brand safety is of paramount concern to advertisers selecting where to allocate their digital marketing budgets. Sprinklr platform partners, advertisers, and customers all need a way to evaluate and understand toxicity in online conversations and the implications for brand safety.
To solve the challenge, Sprinklr is excited to announce a new AI-based Toxicity Model that can help any organization detect the presence of toxicity and measure its reach– when data is available. The AI model goes far beyond simply identifying key words or terms and identifies toxic messages by understanding the context and intent of the message.”
Continued
Twitter provided Sprinklr with a list of 300 english-language slur words. The list of terms was designed to capture hateful slurs and language that targets marginalized and minority voices. Sprinklr analyzed every english-language public tweet between January and February 2023 and identified 550,000 tweets that included at least one word from the list provided.
Our analysis of the Twitter data set provided these findings:
Sprinklr’s AI-based Toxicity Model - Twitter Case Study
We understand that the goal of our partners at Twitter is to understand, measure and reduce toxicity on the platform and to promote brand safety for advertisers. This made Twitter a great early customer and partner for this capability.Twitter provided Sprinklr with a list of 300 english-language slur words. The list of terms was designed to capture hateful slurs and language that targets marginalized and minority voices. Sprinklr analyzed every english-language public tweet between January and February 2023 and identified 550,000 tweets that included at least one word from the list provided.
Our analysis of the Twitter data set provided these findings:
- When compared to non-toxic tweets in the dataset containing slur keywords, toxic tweets received 3 times fewer impressions on average.
- In multiple instances, we observed that the impressions received by toxic tweets were fewer compared to non-toxic tweets written by the same user. For example, a toxic tweet from one particular user received 22 views in comparison to the average of 5K+ views received on other tweets.
- As the Sprinklr Toxicity model understands the context of the slur keyword usage, the majority of tweets with slurs were accurately classified as non-toxic. Some examples:
- Tweet from a major US news outlet - The slur keyword is part of the name of a town
- Tweet from a popular US sports influencer - The slur keyword is part of the name of an individual
- We also identified examples of toxic speech used in the context of a news piece and examples of reclaimed speech from members of marginalized communities
- The percentage of tweets identified as toxic in the data set containing slur keywords was in the range of ~15% over the analyzed time frame. Despite every tweet containing an identified slur word, they are primarily used in non-toxic contexts like reclaimed speech or casual greetings.
Michael O'Herlihy, Director of Product for Trust & Safety at Twitter had this to share:
"For months, we’ve been publishing data on the reach of Tweets that Twitter deems toxic and that contain slurs. Sprinklr’s analysis shows that the reach of toxic content is actually lower than Twitter’s own first-party estimates. Refining our approach to reducing hate speech remains an ongoing commitment."
I'm sure getting rid of verification will work out for Elon, it's not like it blew up in face and pissed off Advertisers last time he tried it.
Dis turnin' into the Dr. Seuss book about the Star-bellied Sneetches...
Twitter Offers New Equity Grants to Staff
Compensation has been one of many questions facing employees since Elon Musk’s tumultuous acquisition of the company last year.
www.wsj.com
So he paid $44 billion for a $20 billion company.
Did Twitter wish to be taken over initially?
Do hostile takeovers usually end with a fair price being paid by the hostile takeover party?
Do people or companies buy other companies for current value or current value plus future consideration value also?
4 months ago, I thought Twitter was worth possibly $5B-$10B.
Good summary
- reached 500 million + total active users
- released new features in the shortest time period in Twitter's history
- became the most downloaded & #1 news app
- improved ad relevance
- removed child porn
- more output with less staff
- reduced bots, scams & hate speech
- improved engagements for advertisers
- exposed truth via Twitter files
- removed censorship
- all time high daily users
- restored free speech
- reduced child sexual exploitation
- community notes debunking propaganda & misstatements
- launched Twitter Blue globally
- introduced verified badges for company accounts
- creator monetization & Twitter payments in making
- open source code for recommended tweets next week
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Would like to see proof that all that happened. Until then it is all bullshit.
Not really.
But Musk shot off his mouth about buying them, and then was contractually forced into following up. Despite trying to back out multiple times.
But Twitter execs saw an offer that was way over-valued and went with the money (which is how capitalism works, btw)
"Future consideration value" here was negative.
And with interest rates rising, Twitter's value - because they were heavily leveraged, was going down. Which is why if someone offers you 1.5x or 2x more than something's worth, and that value is dropping, you sell.
It'd be like buying a house for 2x the listing value, when property values are dropping - quickly.
...not like the Russians or Saudis would want any "source code" to be able to hack Twitter propaganda feedback, Amirite?
I think this is the textbook definition of “winging it.”
He already tried getting rid of "legacy" checkmarks earlier this year in hopes everyone would pay for Twitter and it blew up in his face.
He's got plenty of ideas I don't know why he insists on doubling down on a bad one.
Whoever runs that account seems like a total dumbass. Pretty sure they are a Trumper account.
Kewl
Now Russian bots will determine what's in your User Suggestions feed...
- open source code for recommended tweets next week
GitHub - twitter/the-algorithm: Source code for Twitter's Recommendation Algorithm
Source code for Twitter's Recommendation Algorithm - GitHub - twitter/the-algorithm: Source code for Twitter's Recommendation Algorithm
github.com
...and it's becoming more and more clear those "ideas he doesn't like" are (unsurprisingly) aligned with regimes like Russia, China and Saudi Arabia...
#AmericaAndDemocracyLast
