This is the home for my collection of studies and other data sources on the Musk era of Twitter. There are now 21 studies of Twitter in the Musk era published from November 2022 to the middle of August 2023 in this post, and 5 of the migration from Twitter to Mastodon, for a total of 25 studies (one study fit into both).
I've grouped the 21 Twitter studies into 4 subject categories. This post has a brief overall summary, then a list of the 4 categories, linked to a slightly fuller summary and details of the studies. Right below that list (and before the detailed sections begin), there's a section on background, process, and update history.
This tracker provided the study basis for some of my posts at Absolutely Maybe:
- August 2023: How Is Science Twitter's "Mastodon Migration" Panning Out? (Based on this version);
- June 2023: 17 Studies Plus Advertising Data Map Out Twitter's Decline (4th version of this post).
- Hate speech and online safety [Includes 10 studies]
- Misinformation [Includes 3 studies]
- Other patterns in Twitter use [Includes 8 studies]
- The Twitter to Mastodon migration [Includes 5 studies]
I'll be adding studies as the stream of research on what's happening, broadly defined, grows. Studies added in the last update are marked *. I'd be grateful to hear of studies I've missed. You can use comments here to contact me – I moderate them all, so let me know if you don't want me to publish a message. Or you can talk to me on Mastodon, at @hildabast@mastodon.online.
Other related posts of mine:
- At Living With Evidence,
- Shuffling Communities and Twitter Migration (Nov 2022)
- The Relief of Leaving Twitter (Dec 2022)
- Did the Machines Make Us Do It? (Jan 2023)
- At Absolutely Maybe (PLOS), posts tagged Twitter (including a Twitter timeline and a post on research on quote tweets)
- Posts tagged Mastodon at Absolutely Maybe (including my shortcuts to giving Mastodon a try)
Hilda Bastian.
This is version 5 of this post, dated August 18, 2023.
First version posted on January 30, 2023.
Version 2: Pfeffer 2023 added on February 13, 2023.
Version 3: Bin Zia, Miller, Carniel, and Uni of Michigan (all 2023) added on March 22, 2023.
Version 4: Auten, Chavalarias, Hammer, Hickey, Jeong, La Cava, and Pew Research (all 2023) added on June 4, 2023, as well as an additional study mentioned, but not included – by the Center for Countering Digital Hate (2023c). On June 6, the Iffy Quotient data was updated, and 3 studies by the Center for Countering Digital Hate were added (2022, 2023a, 2023b).
Version 5: Journal versions for Hickey and Jikeli preprints added, and the note for the Bitterman pre-registered study. New studies added: Chang, GLAAD, Jacobs, Siebert, Valero.
Studies of hate speech and online safety
Summary: 5 studies show an explosion of hate speech in the immediate aftermath of the takeover – racism, anti-semitism, and/or homophobia were measured in these studies. For example, the use of some hate speech went from around 80 an hour to well over 4,500 an hour. In another study, hate speech quickly quadrupled, before reducing to a level still much higher than previously.
A further study concluded that Musk's personal tweets appear to be appealing to people who retweet hate groups' tweets. Finally, GLAAD found a major drop in provisions for LGBTQ online safety at Twitter in 2023 compared to 2022.
(Note: Musk took over Twitter on October 27.)
Studies not counted:
If there's no reasonable research report publicly available or at least meaningful information about how data was gathered, I don't include studies. The following 2 were more borderline, so I've detailed them here in case people are interested in them.
(1/2) Center for Countering Digital Hate (2023c).
This study involved the CCDH reporting 100 tweets promoting hate from Twitter Blue users. I couldn't find enough detail about the methods for this, and what's reported shows some biases. For example, there's no control data, and Twitter's actions only within 4 days of the reports are reported. (Only 1 of the tweets were taken down in that time, and the tweets were still apparently getting boosted by Twitter's algorithm favoring Twitter Blue.)
(2/2) Washington Post article by Joseph Menn discussing unpublished research (2023).
This article discussed upcoming research suggesting that hate speech on Twitter coincide with increases in anti-semitic and homophobic violence in the US, but there wasn't enough information to weigh that conclusion.
Included studies, from the most recently published:
* GLAAD (2023).
GLAAD, a LGBTQ advocacy organization in the US, analyzed 5 social media platforms in 2022 and 2023, using a Social Media Safety Index (SMSI): Facebook, Instagram, TikTok, Twitter, andYouTube. Each of them is rated on a score with12 indicators for policy and practice in a scorecard, and the companies are contacted to review their data. Twitter came last of the 5 by a long way – scoring 33% compared to Instagram's 63%. That was a drop of 12 points from the previous year – the other 4 each had an increase (of between 9 and 15 points).
Trevor Auten (2023).
This is a masters thesis. Using data from Twitter's API, Auten created networks of tweets from 1 week in 2021 and 1 in 2022, 6 weeks after Musk's takeover, and looked at the relationship between Musk's own Twitter account and those of hate groups (3 types: White nationalists/alt-right, anti-semites, and anti-LGBTQ). He concluded that people who retweet hate groups' tweets were also more likely to retweet Musk's tweets, suggesting that Musk's rhetoric is encouraging to hate groups.
Daniel Hickey and colleagues (2023a preprint; *2023b paper).
The authors created a lexicon of 49 keywords for hate speech, supplemented with a filter for detecting toxic content to identify "a rude, disrespectful, or unreasonable comment that is likely to make people leave a discussion," and filter out porn (the Perspective API). After identifying a group of tweets between October and November 2022 from the Twitter research API that met their criteria, the researchers collected all the tweets from those accounts in the month before and after the Musk takeover. They also identified a control group the same way (using non-hateful tweets), and used Botometer to look for bot activity.
The hateful tweeters' hateful tweets quadrupled after the takeover, then settled back to a level higher than previous to the takeover.
Scores for bot activity changed. While the overall amount of bot activity remained similar, spammer and fake follower accounts increased for both hateful and control accounts, while astroturf bot activity decreased for the control accounts. (Astroturf bots here were ones that artificially inflate support for political candidates and smear opponents.)
Center for Countering Digital Hate (2023b).
This is based on a search of tweets that used both a keyword for LGBTQ+ together with any of 3 specific slurs (while excluding wedding/marriage terms). The researchers used SNScrape (Python code for scraping Twitter). They did not use any other method (such as a filter) to determine how often the context was hate speech. That's critical, because people can use a term to call out someone else's hate speech.
The researchers identified over 1.7 million such tweets between January 1, 2022 and February 28, 2023. Before the takeover, the average was over 3,011 per day, rising to 6,596 after the takeover.
They concluded that 5 accounts are driving the "grooming" slur on Twitter. From December 15, when Twitter began releasing tweet impressions, to the end of February, tweets from those 5 accounts were getting an average of over 18 million impressions daily. (Impressions are the number of times Twitter serves the tweet into a timeline or search.)
Screenshots of ads from major companies appearing on those accounts are included, along with an estimate of how many millions in advertising revenue Twitter could be making on these accounts alone over a year.
Center for Countering Digital Hate (2023a).
This is a tally of "tweet impressions" for 10 reinstated Twitter accounts. Tweet impressions are the number of times that a tweet has been served in a timeline or search result. The accounts had previously been banned for hateful activity, misinformation, or both.
The 10 accounts posted 9,615 tweets from December 15, 2022 to January 30, 2023, with over 2.5 billion impressions – averaging over 54 million a day – with 1.6 billion of them for a single account.
Screenshots of ads from major companies appearing on those accounts are included, along with an estimate of how many millions in advertising revenue Twitter could be making on these accounts alone over a year.
Carl Miller and colleagues (2023).
This study classified tweets, using Twitter's API, identified by language models as "plausibly antisemitic", in English only. Between June 1 of 2022 and February 9 of 2023, there were 325,739 of these tweets sent from 146,516. Before the takeover the weekly averages was 6,204. Afterwards, the weekly average was 12,762.
The researchers found a significant surge in new accounts posting these tweets: 3,855 such accounts were created in the week after the takeover.
While some of these tweets are being taken down, possibly by Twitter, the rate of takedowns did not keep up, according to the researchers, "with the increases in absolute volume of antisemitic content."
Bond Benton and colleagues (2022).
A study of the use of a previously moderated homophobic slur before and after the mass shooting at an LGBTQIA nightclub in Colorado on November 19/20. The authors analyzed tweets from November 15 to November 23. They used Tweet Binder, a Twitter analytics marketing service.
The authors explain the QAnon context of the use of forms of the term, groomer. There was some increase in use of the term in the days before the shooting, and then a dramatic increase in the use of the term after the shooting, both as homophobic slurs and denouncing those tweets. The authors concluded, "Cumulatively, results would seem to indicate what results of a less stringently moderated Twitter may look like."
Gunther Jikeli and Katharina Soemer (2022, *2023).
A study of anti-semitism on Twitter between January and November 2022, with a focus on October 1 to November 6, "when the number of conversations about Jews more than doubled," and the period after Musk's takeover. Several millions of tweets are included. Of the more than 100,000 about Jews in the first peak after Musk's takeover (October 30), the authors randomly sampled and annotated 100.
Most tweets were decrying anti-semitism, but there was an increase in anti-semitic tweets. They concluded that some users were trying out whether they could use a particular slur in the new Twitter.
(This study presumably used Twitter's API – they say they "scraped" tweets from "the Twitter archive.")
Center for Countering Digital Hate (2022).
This is a fact check of a Musk claim about hate speech declining at Twitter in November 2022. They used a social media analytic tool, Brandwatch, to gather data on the frequency of tweets using a slur (from a list of 6 related to race and sexuality) and retweets of them in the week beginning October 31, compared to the 2022 average. However, they did not use any other method (such as a filter) to determine how often the context was hate speech. That's critical, because people can use a term to call out someone else's hate speech.
The Center identified a major increase in the use of these words, up to triple.
The report includes a link to a tweet from Twitter's then-head of trust and safety (Yoel Roth) acknowledging that there had been a surge in hate speech, but the team had succeeded in reducing the prominence of these tweets, so that they did not spread as much.
Bond Benton and colleagues (2022).
A study of the use of particular hate terms (eg racist, anti-semitic, and homophobic slurs) from October 22 to October 28, with sentiment analysis (estimating whether or not the use of the word was hostile).
The hate speech they tracked went from 80 tweets an hour before the takeover to well over 4,500 an hour afterwards. The researchers used the Tweet Binder tool.
Misinformation
Bastien Carniel and colleagues (2023).
This study was based on a database of websites labeled as propagators of misinformation by fact-checking organizations in multiple countries and languages. A list of 514 Twitter accounts were labeled misinformation superspreaders, as they repeatedly shared links from these websites. Those superspreaders tweeted 1.5 million times between September 1 and December 31, 2022 (before and after the takeover). For comparison, the researchers collected over 640,000 tweets from 130 traditional media Twitter accounts.
The researchers found a small drop in engagement with the tweets from traditional media (– 6.3%) and a large increase in engagement with the superspreaders (42.4%): "Immediately after the acquisition, total engagement with tweets posted by superspreaders spiked, almost doubling overnight and remaining at elevated levels ever since. Since the number of tweets from these accounts has remained roughly constant, this jump is only explained by an increase in the average engagement with these accounts' posts."
Other patterns in Twitter use
Note on baseline data: Musk took over Twitter on October 27. Jürgen Pfeffer and colleagues (2023) collected a complete 24-hours' of tweeting before the Musk takeover. On September 21, 375 million tweets were sent from over 40 million accounts. About 1% of the tweets came from less than 100 accounts, and roughly 175,000 accounts (0.44% of accounts) produced 50% of the tweets.
Studies, from the most recently published:
* Myriam Vidal Valero (2023).
In this study for a journal news feature, a database of email addresses of over 170,000 corresponding authors who had tweeted about their own publications was used. (The database had been compiled by Wenceslao Arroyo-Machado and colleagues for other analyses [2023]. The authors had been identifiable in February 2023, and the papers – gathered from the Web of Science – covered over 250 disciplines.)
The authors were emailed in July, and asked if their Twitter use had changed in the previous 6 months, and if they had opened accounts on any other social media platform in the previous year. The response rate was extremely low – about 5% – and no data is provided to give an idea who the 9,153 respondents were, and how they compared to non-respondents.
Of the respondents, 7% said they had stopped using Twitter, 24% that their use had "significantly decreased", and 23% that it had "slightly decreased". Of the other half, most said their use hadn't changed (37% of the total), while for 9% it had increased significantly (3%) or slightly (6%).
Nearly half (46%) said they had opened a new social media account in the previous year. The social media platforms with proportions of these scientists in the 2-digits were:
- Mastodon (47% - 1,976 scientists)
- LinkedIn (35%)
- Instagram (29%)
- Threads (25%) (it had just rolled out at the time of the survey)
- Facebook (22%).
* Jay Jacobs (2023).
This is an analysis of tweets from the Twitter API for Infosec Twitter – discussions on common information security vulnerabilities. Tweets (but not retweets) with particular keywords had been collected from 12 July 2021, ending in July 2023 when charges for the data were introduced.
Across that time, there had been over 1,200 of those tweets each week day, and under 500 on weekend days. There was no major change in the first few months after the takeover. However, from April to May 2023, Jacobs describes Infosec Twitter as dying. By the last 2 weeks, there were less than 300 tweets a week day. He wrote, "And with that, we say 'so long' to infosec Twitter."
* Charlotte Chang and colleagues (2023).
In this study, the authors compare 380,000 participants in "Environmental Twitter" (frequently posting about biodiversity and mitigating climate change) with a control group of 458,000 participants in what they called "Politics Twitter" (accounts posting on the 2020 US presidential election). Commenting on that election was so widespread, the authors believed those accounts represented "a broader slice of Twitter as a whole". (The accounts tweeting on both subject areas were deleted from the "Politics Twitter" group.)
The authors analyzed the proportion of accounts that were active in each 15-day period between July 2019 and April 2023, with active defined as an existing account tweeting at least once in the period. The data was grouped into pre- and post-takeover samples. By April 2023, 53% of the "Environmental" group were still active versus 79% of the "Politics" group, with a rapid decline from the time of the takeover.
The authors don't report the language of the accounts, but it appears to be English-speaking Twitter. Nor do they report the geographical spread, so it's not clear if a more international group is being compared to a more US-based group.
Luca Hammer and Martina Schories (2023). (In German – this is my own translation.)
This is a study of over 1.2 billion tweets in German between December 2020 and May 2023, with a gap of several months at the start of 2023 because of access issues with Twitter's API. The researchers estimate the sample is around 90% of all German-language tweets. There is information for over 4.2 million Twitter accounts, and follow networks for March 2023 of over 600,000 accounts that had tweeted more than 100 times in the sample.
The researchers determined that the data for April were the highest quality in 2023, so they compared April data from 2021, 2022, and 2023. The number of tweets dropped from close to 4 million that month in 2021 and 2022, to just over 3 million in 2023. There were over 1.5 million tweets per day in April 2023. However, right-wing accounts posted 64% more tweets in April 2023 than in April 2021, the only cluster with a major increase in tweeting. Otherwise, people's bubbles on Twitter were getting smaller, and people were tweeting less.
Pew Research Center, American Trends Panel survey, Wave 123 in March 2023 (2023b, 2023c).
This is a survey of 10,701 people drawn from a representative panel of internet users in the US, with Asian, Black, and Hispanic users oversampled. (Methods.)
Although Twitter-using respondents from this panel in 2021 hadn't differed much along partisan political lines on whether civility or misleading information were a major problem on Twitter, they were very divided in March 2023. From 36-39% believing incivility was a major problem in 2021, 50% of Democratic users said it was in 2023 vs 27% of Republican users. From 52-54% believing misinformation was a major problem in 2021, 68% of Democratic users said it was in 2023 vs 37% of Republicans.
More Democratic users than Republican ones believe harassment and abuse from other users is a major problem: from 50% of Democratic users in 2021 to 65% in 2023, vs 41% of Republican users in 2021 dropping to 29% in 2023.
They report that 60% of Twitter users said they had taken a break of weeks or months from Twitter in the past year, with women more likely to (69% vs 54% of men). Black users were also more likely to say they took a break than white users (67% vs 60%). However, there was no context to interpret this, as the researchers didn't report a comparison question from past surveys, or a difference before and after the Musk takeover.
Asked if they expected to be using Twitter a year from now, 25% said they were not very likely to, or not at all. The rate of Democratic women saying this, however, was 35%. Again, there were no comparisons from the past, or pre- and post- the Musk era. Overall, the rate for Democratic users was 29% versus 20% of Republican users.
Note: Democratic above is a combination of Pew's "Democratic and Democratic-leaning"; Republican, "Republican and Republican-leaning."
Pew Research Center, American Trends Panel survey, Wave 119 in December 2022 and respondents' tweets from January 2022 to April 2023 (2023a).
This is a survey of 11,004 people drawn from a representative panel of internet users in the US. (Methods.) The researchers also used Twitter's API to collect respondents' tweets from January 1, 2022 to April 10, 2023.
Awareness of the Musk takeover was high: About 40% had mentioned Musk in a tweet or tweets since early 2022, particularly Republican Twitter users.
As usual, a minority of people do the bulk of the tweeting: 20% of this group posted 98% of the tweets. The bulk of them were Democratic users (61%) – again, similar to previously. However, 20% of the most active tweeters before the Musk takeover were no longer among the most active after it; and a quarter of the top 10% before were no longer so after the takeover. And the most active users were also tweeting less (about 25% fewer tweets).
Note: Democratic above is a combination of Pew's "Democratic and Democratic-leaning"; Republican, "Republican and Republican-leaning."
Jonathan Schulman and colleagues (2023).
More than 24,000 Americans were surveyed in December 2022/January 2023. Surveys had also been run at 3 prior points in the 2022, each with over 20,000 participants. There was an overall drop of 3 percentage points in people reporting they used Twitter – or roughly 10% of individual users. Democrats had been at 37-38% at each of the earlier 3 time points, but were 33% in December/January. The authors concluded:
"This decline was driven by Democrats. For Republicans and independents, there were statistically insignificant declines in Twitter usage between the two surveys, but the percentage of Democrats fell from 38% to 33%. Prior to Musk purchasing Twitter, our surveys had shown reported Twitter usage to be stable within each party, where Democrats and independents have been consistently more likely to report using Twitter than Republicans.
Despite the decrease in usage and trust of Twitter by Democrats since Musk’s takeover, there were no significant changes among Democrats in reported usage of Twitter specifically as a source for political news. There was an increase in the share of Republicans who reported using Twitter as a source of news, from 10% to 14%."
Christopher Barrie (2022).
From November 9-11 there was a release of paid "blue check" subscriptions, and this study used a database of 138,000 Twitter users that signed up. The author looked for 1,000 of those accounts with close connections to far right networks (from another database) and found 961 of them, with around 4.8 million tweets between May 17 and November 23, 2022. He also looked at tweets from 933 users from the "blue check" database that were not in the far-right-associated database.
The 961 contentious users had a 70% increase in retweets after the takeover; the other 933 had a 28% increase. (This study couldn't assess overall engagement on Twitter in that time period.)
Twitter to Mastodon migration
- Mastodon (47% - 1,976 scientists)
- LinkedIn (35%)
- Instagram (29%)
- Threads (25%) (it had just rolled out at the time of the survey)
- Facebook (22%).
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