Post
Topic
Board Altcoin Discussion
Re: Machine Learning for identifying SCAM NFT Games
by
bitcoinnews_id
on 08/03/2022, 17:39:22 UTC
Some important items to consider:

  • It may be good to produce a risk score instead of claiming something is a scam until there are clear evidence. Factors that could impact a risk score are items you mentioned, as well as when contracts are involved the audit reports. A factor that will be very difficult to program is the gut feel of the idea. The idea may sound good but on closer inspection it seems at some point there will be division by zero proverbially speaking or lead turned into gold, that should count a lot. A particular issue for me is the project claims that there will be payouts in a stable coin but they don't say where the stable coin funds will come from.
  • When is something considered to be a scam and when is it not - for example, dev does a rug pull or exist with the funds and the project died, funds were obtained but the dev team ran out of funds and the project died,  there was no community interest and a project died, some government shut something down and the project died, a dev team had a great idea but poor strategy and execution and the project died etc.
  • What data will be used for he machine to learn eg will you use attributes from past confirmed scams?
  • At which point do you confirm a project is a scam. There are projects that have been going on for years but is not progressing a lot with some people claiming scam and others clinging to hope

I totally agree with what @jc12345 has said that I quoted. Let me add a little thing, that the project is more perfect in encapsulating the end goal of the creator. Indicators that will be studied must really have shown previous evidence. So that your claim to the results of your research is not ambiguous. You can test your research results with many methods such as confusion matrix to determine how accurate and precise it is. I know this will be very difficult to run, you have to find and collect data to create your own dataset because it is not available on the internet or libraries.

If this research can be done according to your hypothesis, then find a way and finish it. I hope you find new insights and contributions to technology and education.