Quote from: Maus0728 on Today at 01:48:57 AM

Hi everyone!

I just wanna ask if there's interest in an application that uses machine learning to identify potentially fraudulent NFT games. Machine Learning is basically an approach in which we feed raw data to an application/machine and it learns something on its own[1]. And I understand that there is a lot of data to examine, such as their website, github repository, whitepaper and fake team to be utilized as Artificial Intelligence training data, and so on...but is there even a demand for it? Is this a worthwhile research project?

On the other hand, I discovered a previous study[2] that utilizes the similar process but instead of NFT, they identify scam ICOs, which provides me an idea for this study's topic. With the NFT games at peak, will this topic be helpful in many ways?

[1] https://www.expert.ai/blog/machine-learning-definition/#:~:text=Machine%20learning%20is%20an%20application,it%20to%20learn%20for%20themselves.
[2] https://arxiv.org/abs/1803.03670

*Self moderated for unconstructive posts*

Being able to tell if something is a scam with more certainty is really something that is needed. Although there are current indicators to guide us it is never possible to tell with 100% certainty and there is always a risk of something being a scam, but sometimes it only materializes after the scam occurred. An indicator you mentioned is having a whitepaper, but not having a whitepaper does not mean it is a scam, it just adds to the risk score.

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
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