Crypto: How The Sentiment Analysis Tools Work And Why People Use Thembr>
It can’t be denied that there are more than enough tools for trading cryptocurrencies than there’s demand for. Every time somebody checks GitHub there’s always some kind of AI or 100% correct calculation tool which will help traders in their daily investment decisions.
Naturally, it becomes a little bit hard to decide which one you should go for as the promotion of these tools is either very hard to find or non-existent. Most of the tools that get promoted online belong to a crypto exchange or a large corporation, while private ones tend to be on the scammy side.
Because of this, many crypto traders who are developers themselves decided to make their own trading tools. One or two successful trades later they thought it was a great creation and are now trying to sell it to other traders.
In general experience though, it’s been proven that keeping up to date with important news and studying charts is usually the only tool you’ll ever need, but they also tend to take quite a lot of time.
Therefore, people tend to use analysis tools that have nothing to do with trading but allow them to digest most of the important news that comes out on a daily basis. These tools are also not 100% accurate, thus not very reliable, but getting overall sentiment is still quite useful.
What do these tools do?
The sentiment analysis AI is basically like a compilation of data with assigned meaning. For example, it can be used to determine the sentiment of the crypto community towards Libra. Is it negative? Or is it positive? Through the compilation of a specific website’s posts, that much can easily be determined.
The most popular website to use it on is Twitter, as that’s where most individual statements about cryptos are made almost every day. Actually, that’s one of the main places where people can get instant access to fresh news.
How they work
These tools were first developed by crypto exchanges themselves in order to increase their daily trading volume and get more people interested in trading with them.
In fact, the developers that work on these tools are sometimes hired from casino software providers as the algorithms are very similar. The algorithms that real money online slots in AU use, in particular, are mostly adaptable to the same goals that sentiment analysis tools have.
Here’s how they’re usually designed to work
The developer needs three tools in order to get the results it needs from this software. These are the API of a specific social media platform, a lexicon library that can identify all of the words in a specific language, and a little knowledge in Python (preferably).
The first thing that needs to be done is the identification of the keyword. This can be something like Bitcoin, crypto, blockchain or pretty much anything else that refers to cryptocurrencies. There can even be multiple of these keywords.
Once it has been identified, the AI will scan the API in search of posts that have these keywords and compile them together.
The next command that the developer types in are the tokenization of these posts. This means that every word in the post becomes an element that the AI scans. Thanks to the lexicon library that’s attached to the software, it can immediately identify all of the words and even typos.
The lexicon library usually comes with “approval ratings” for each word. For example, negative, positive and neutral.
The AI, once it has assigned these ratings to each token, compiles them into a sentence and takes context and syntax into consideration.
In the end, it can identify whether the poster is referring to the keyword in a negative, positive or neutral manner.
The rankings are between -1 (very negative) and 1 (very positive). The AI does this to every single post-it identifies with the keywords (within a certain timeframe, like since last month or something) and calculates the average number. For example, if the final score for “Bitcoin” is -0.1 it means that the community is a bit more negative on the matter, which could lead to the price dropping. If it’s 0.1 it means that there’s still positivity.
But, the AI can’t really read through things like sarcasm or referrals to various events in the industry, thus this analysis is not 100% correct, but still a good additional tool for a trading strategy. The most effective indicator for market movements would be volume rather than what investors think about the future of a specific asset.