Awful post.

In case anyone is wondering this image is from a Oct 2025 tweet (at least, that was the oldest tweet I could find for it) that claims:

A new independent investigation by Social Forensics, funded by the National Iranian American Council (NIAC), has exposed an extensive Israeli government-linked network of fake Twitter accounts built to dominate Persian-language discourse and amplify anti-Iran narratives after the 2022 death of Mahsa Amini.

The report analyzed 1.5 million tweets from 213,000 accounts, uncovering a web of coordinated inauthentic behavior designed to manipulate perceptions of Iran and flood social media with anti-government sentiment.

The data shows that nearly half the accounts were created in 2021–2022, and a quarter appeared after Amini’s death, suggesting state-backed mass production of bot accounts. Many featured crown emojis and Reza Pahlavi slogans, posing as monarchist supporters to fabricate the illusion of a massive anti-regime movement.

Here’s the PDF it actually comes from which dates it July 2023 (again, can’t verify this - I only found it by searching for the image). The Social Forensics website doesn’t mention it under Our Work but they do have a post from the same year about the Iranian ‘twittersphere’ in general: https://www.socialforensics.com/our-work

https://static1.squarespace.com/static/5d430ca0949c3a0001d9da65/t/6504765336c56b48f69ad786/1694791271151/Social-Forensics-Iranian-Twittersphere-July-2023-2.pdf

From the PDF:

Disinformation and platform manipulation researchers will often talk about how bad those problems are in the United States and Western Europe, especially in the English-speaking world. They will often then talk about how much worse it is abroad, in Brazil, Spanish-speaking countries and India, for example.

In China, The Washington Post reported how the Chinese government itself flooded Twitter with keywords to drown out news and images of last year’s protests against coronavirus restrictions. Elon Musk, who took over Twitter in October 2022, has vast investments inside China. Prior to Musk’s takeover, there was a team of Twitter employees focused on mitigating deceptive foreign influence operations.

Due to mass layoffs and resignations, however, that team has been “reduced to a handful of people or no staff at all.”

What researchers who know Iran will also say is that Iran is a no-man’s land for platform manipulation and disinformation because multiple world powers – including the United States, Russia, China, Saudi Arabia, the UAE, and Israel – are playing inside the country, as is the IRGC. The Iranian government’s chief interest is self-protection and not the protection of its citizens, hence multiple governments have cyber capabilities running inside the country.

Thus the Iranian Twittersphere is one of the most heavily manipulated corners of Twitter, where hashtag manipulation – as well as targeted abuse – have been rampant for years.

In September 2022, after the death of Mahsa Amini at the hands of Iran’s morality police, platform manipulation directed at the Iranian diasporic community increased significantly.

An investigation conducted by Social Forensics has uncovered evidence that online disinformation, smears, and threats against the Iranian diaspora (particularly in the U.S. and Europe) – ranging from journalists to academics to foreign policy analysts to civil society members – is:

1. At a scale and level of sophistication suggesting state-actor involvement

2. Driven by or significantly amplified through platform manipulation

3. Linked to foreign states that opposed the JCPOA and any U.S.-Iran detente, and have lobbied for the U.S. to take a more hawkish approach to Iran

The following report outlines our research process, summarizes our findings, and provides historical context to strengthen our conclusion – namely, that the surge in platform manipulation across the Iranian Twittersphere after the death of Mahsa Amini has been driven by state-sponsored efforts.

From the PDF about the actual image in the post:

Following/Followers relationships were mapped for a subset (53K) of the 213K accounts from our Mentions Dataset. The 53K accounts were sourced from the following 3 segments: 1) attacks on Rana Rahimpour after the IRGC released a personal conversation between her and her mother which was later edited and then amplified by Saudi-funded Iran International, 2) attacks on Farnaz Fassihi for covering Iran for The New York Times, and 3) attacks on Negar Mortazavi in the days leading up to a bomb threat that was called into The University of Chicago, where she was scheduled to be hosted on a panel at the university’s Institute of Politics

Nearly 2 million relationships were used to construct this network graph visualization of 53K accounts: Colored communities (7) are determined algorithmically (Louvain method), whereas the community labels, on the other hand, involve a manual process of reviewing tweets and (Following/Followers) relationships from a sampling of accounts from each community. The community labels should be viewed as best-fit descriptions, rather than ones that can accurately be applied to every single account from each respective community.