Types of abuse, such as plagiarism, AI-generated content, and spam, negatively impact Steem's reputation, devaluing the quality of content and reducing user trust. Therefore, communities must ensure the well-being of the platform by detecting and reporting these cases. On the other hand, automated voting encourages abuse by users seeking to take advantage of the reward system.

Steem Watcher supports communities in maintaining a safe environment on the platform, where the content policy is respected.

• To date, I have reported 2,295 cases of abuse involving 1,133 users. In October, we removed $2,678,331 in downvotes against blacklisted users.

_Pixabay

Below I share the cases that were detected and validated as abuse, most of the accounts are related to a farming community.

No.	Post Link	Source	Abuser ID	Abuse Type
@do-the-dance (*)	POST LINK	Source Link	AI Content	@scrutinize
@cryptid003 (*)	POST LINK	Source Link	AI Content	@scrutinize
@find-god (*)	POST LINK	Source Link	AI Content	@scrutinize
@funding-holiday (*)	POST LINK	Source Link	AI Content	@scrutinize
@fool-x-rated (*)	POST LINK	Source Link	AI Content	@scrutinize
@freezing-ice (*)	POST LINK	Source Link	AI Content	@scrutinize
@dying-giraffe (*)	POST LINK	Source Link	AI Content	@scrutinize

(*) Reported for the first time.

Each content goes through a variety of tools that serve to verify the authenticity of the content of each publication.

Search Tools.

Plagiarism Detectors	AI Content Detectors
quetext	openai
etxt.biz	zerogpt
plagiarismchecker	gptzero
plagiarismdetector	contentatscale
check-plagiarism	Paraphrasingtool
prepostseo	Crossplag
smallseotools

To conclude my report, it is necessary to point out that in each case identified, I leave in the comment a link to the @abuse-watcher publication where some information and advice on plagiarism and abuse is shared.