> For the complete documentation index, see [llms.txt](https://sonart.gitbook.io/sonart/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://sonart.gitbook.io/sonart/1.-hype-analysis-powered-by-a.i..md).

# 1.      Hype Analysis powered by A.I.

Before investing in any collection, all smart flippers take a good, hard look at the hype surrounding it. Measuring the hype from Twitter is crucial to invest in NFT’s. 

This is especially true for new collections before mint where there is no other data available, such as volume, number of sales or holders information. 

However, distinguishing between fake and real hype can be difficult, as there are an increasing number of bots and fake accounts on Twitter, and manipulative transactions on Opensea. 

This A.I. system retrieves all available information on a targeted Twitter account and all the associated transactions on OpenSea – if available. 

Once setup, it can detect a true hype very early on by detecting acceleration of volume of trades, number of tweets, analyzing their sentiment towards the collection while removing bots account from the analysis. 

This A.I. will save you countless number of hours in terms of work and research. 

How does it work? In a nutshell, this A.I. system will:

* Extract all tweets and replies mentioning the official accounts
* Extract information and transactions on Opensea account - if available
* Apply a Sentiment Analysis model on every tweet and reply to determine if the mention is positive, neutral or negative
* Apply a detection bot model to spot fake accounts
* Filter out tweets, replies, likes, RT from these fake accounts
* Aggregate the remained accounts to get statistics (like number of true unique accounts, etc.)
* Output a hype score based on past data and state-of-the-art algorithms

*Now that you know how it works, you have no excuse to fail your flips anymore!*

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