I talked to people behind two escort services’ spam accounts, both said that they provide escorts and use ad services on Twitter. One said they have no connection with the Chinese government, and said they also promote their services on Facebook and Instagram.

I also contacted an ad service seen in two spam posts and received a rate sheet. This business charges about $1,400 a month for an ad campaign on Twitter involving 200 bot accounts that will tweet at least 150 times a day.

Rate sheet:

The findings match a report published today by @det from Stanford Internet Observatory who reviewed millions of tweets by searching for 30 Chinese cities and found that bots were active before the protests began and continued after they had ebbed.

https://cyber.fsi.stanford.edu/io/news/content-moderation-survivor-bias

We searched on Twitter for 16 cities and reviewed the results for spam. When we did the searches in simplified Chinese, bots were active throughout, for Chinese cities with or without protests as well as for foreign cities.

When searching the city names in English, the results returned no spam among top tweets.

The comparison underscores the inefficacy of Twitter and other large American social media platforms’ content moderation work on non-English posts.

https://www.nytimes.com/interactive/2022/12/19/technology/twitter-bots-china-protests-elon-musk.html

@det and us both did two queries. Mr. Thiel did one on Nov. 29 and one on Dec. 4. We did it on Dec. 2 and Dec. 6. We all observed a “surge” in the days immediately prior to every execution of the search query, “illustrating the unmoderated content bias.”

We found no evidence backing the idea that the ad campaigns are carried out by the Chinese government.

Some analyses done around the end of Nov into this Chinese-language bot activity observed a “surge” from around the time when protests started, which invited the theory that it might be a deliberate information campaign.

@det explained this recency bias. "In retrospective research, historical Twitter data generally becomes 'cleaner' — some amount of spam and inauthentic behavior will have been removed...inauthentic content tends to appear most prevalent in the immediate past."