Twitter is wrong: facts are not enough to combat Alex Jones

"Did We Create This Monster?" How Twitter Turned Toxic - Fast Company

For years, the company’s zeal for free speech blinded it to safety concerns. Now it’s scrambling to make up for lost time.

Jack Dorsey Has No Clue What He Wants

A Q&A with Twitter's CEO on right-wing extremism, Candace Owens, and what he'd do if the president called on his followers to murder journalists.

America’s Right-Wing Propaganda Problem Might Be Terminal - Dame Magazine

America’s descent into mass delusion isn’t happenstance. The demise of courageous journalism isn’t a happy accident. Its replacement with engagement-chasing infotainment and propaganda isn’t an error. It’s a global assault on reason and informed consensus, and corporations and authoritarian bullies like Donald Trump are both architects and benefactors. For decades, academics warned anybody who’d listen

The Media Can't Stop Propping Up Elon Musk's Phony Supergenius Engineer Mythology

"CEO said a thing!" journalism is now utterly pervasive, and includes parroting billionaire and CEO claims with a total disregard for whether or not anything being said is actually true.

Who’s really being silenced on Twitter?

It’s not who Trump thinks it is

Evaluating Twitter’s algorithmic amplification of low-credibility content: an observational study

Artificial intelligence (AI)-powered recommender systems play a crucial role in determining the content that users are exposed to on social media platforms. However, the behavioural patterns of these systems are often opaque, complicating the evaluation of their impact on the dissemination and consumption of disinformation and misinformation. To begin addressing this evidence gap, this study presents a measurement approach that uses observed digital traces to infer the status of algorithmic amplification of low-credibility content on Twitter over a 14-day period in January 2023. Using an original dataset of ≈ 2.7 million posts on COVID-19 and climate change published on the platform, this study identifies tweets sharing information from low-credibility domains, and uses a bootstrapping model with two stratifications, a tweet’s engagement level and a user’s followers level, to compare any differences in impressions generated between low-credibility and high-credibility samples. Additional stratification variables of toxicity, political bias, and verified status are also examined. This analysis provides valuable observational evidence on whether the Twitter algorithm favours the visibility of low-credibility content, with results indicating that, on aggregate, tweets containing low-credibility URL domains perform better than tweets that do not across both datasets. However, this effect is largely attributable to a difference in high-engagement, high-followers tweets, which are very impactful in terms of impressions generation, and are more likely receive amplified visibility when containing low-credibility content. Furthermore, high toxicity tweets and those with right-leaning bias see heightened amplification, as do low-credibility tweets from verified accounts. Ultimately, this suggests that Twitter’s recommender system may have facilitated the diffusion of false content by amplifying the visibility of low-credibility content with high-engagement generated by very influential users.

Evaluating Twitter’s algorithmic amplification of low-credibility content: an observational study

Artificial intelligence (AI)-powered recommender systems play a crucial role in determining the content that users are exposed to on social media platforms. However, the behavioural patterns of these systems are often opaque, complicating the evaluation of their impact on the dissemination and consumption of disinformation and misinformation. To begin addressing this evidence gap, this study presents a measurement approach that uses observed digital traces to infer the status of algorithmic amplification of low-credibility content on Twitter over a 14-day period in January 2023. Using an original dataset of ≈ 2.7 million posts on COVID-19 and climate change published on the platform, this study identifies tweets sharing information from low-credibility domains, and uses a bootstrapping model with two stratifications, a tweet’s engagement level and a user’s followers level, to compare any differences in impressions generated between low-credibility and high-credibility samples. Additional stratification variables of toxicity, political bias, and verified status are also examined. This analysis provides valuable observational evidence on whether the Twitter algorithm favours the visibility of low-credibility content, with results indicating that, on aggregate, tweets containing low-credibility URL domains perform better than tweets that do not across both datasets. However, this effect is largely attributable to a difference in high-engagement, high-followers tweets, which are very impactful in terms of impressions generation, and are more likely receive amplified visibility when containing low-credibility content. Furthermore, high toxicity tweets and those with right-leaning bias see heightened amplification, as do low-credibility tweets from verified accounts. Ultimately, this suggests that Twitter’s recommender system may have facilitated the diffusion of false content by amplifying the visibility of low-credibility content with high-engagement generated by very influential users.

Do social media threaten democracy?

Facebook, Google and Twitter were supposed to save politics as good information drove out prejudice and falsehood. Something has gone very wrong

The Future of Twitter: Q&A with Jack Dorsey

An in-depth conversation on 10 years of tweeting, the importance of live media, and “the puddle.”

Data Feminism for AI

Attacks on women and trans people are not happening in a vacuum. Communications scholars W. Lance Bennett and Marianne Kneuer recently argued that we are witnessing the intensification of "illiberal public spheres" around the world (Bennett and Kneuer, 2023). These are characterized by a set of anti-democratic communications tactics that include the denigration and exclusion of minoritized people, targeted attacks on the press and political institutions, and transgression of norms of civil discourse. Such tactics are enabled and amplified by the social media platforms owned by Big Tech, whose business model elevates attention above all other metrics, such that they profit richly off extremism, threats, spectacle, and lies. The success of this corporate partnership with right-wing extremism is evident in the proliferation of book bans (Magnusson, 2024), the demonization of DEI and critical race theory (Crenshaw, 2022), and mob tactics to doxx, intimidate, misrepresent, and otherwise silence people that study misinformation, speak out against racial and gender violence, or rule against insurrectionists (Edmonds, 2024). At the same time, we have seen the continued work of feminists, including Latin American, Indigenous, and abolitionist feminists in the US and globally, doing the work of imagining alternate worlds (Cullors, 2021; Davis, 2022; Ricaurte, 2019; Simpson, 2017). This paper represents our own first attempt to imagine a more equitable, sustainable, feminist world for AI research.

No, The FBI Is NOT ‘Paying Twitter To Censor’

Sigh. Look. I want to stop writing about Twitter. I want to write about lots of other stuff. I have a huge list of other stories that I’m trying to get through, but then Elon Musk does someth…

I Speak Fluent ‘New Social Media CEO Who’s In Over Their Head’; Let Me Translate The Last Few Days Of Twitter Policy

The last few days on Twitter have been, well, chaotic, I guess? Beyond the blocking of the ElonJet account, followed by the blocking of the @JoinMastodon account, then the blocking of journalists a…

Study finds persistent spike in hate speech on X - Berkeley News

The new analysis contradicts the social media platform’s claims that exposure to hate speech and bot-like activity decreased during Elon Musk’s tenure.

Opinion | Twitter Has an Old Media Problem. Here’s a Solution. (Published 2016)

The company has become an indispensable news source for millions but as a business, it needs a white knight to swoop in.

How a single tweet transformed the AI safety debate

Most people think AI is risky, but they don’t agree what to do next.