In search of abusers // Weekly Report 189 // 28-08-2025
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.

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 |
---|---|---|---|---|
1 | Link | Link | @nicevday.tagai | Reward Farming |
2 | Link | Link | @aprtoken.tagai | Reward Farming |
3 | Link | Link | @babymarke.tagai | Repeat Content |
4 | Link | Link | @aprtoken.tagai | Reward Farming |
5 | Link | Link | @aprtoken.tagai | Reward Farming |
6 | Link | Link | @tt0xtagai.tagai | Reward Farming |
(*) 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.