Trading 101: Sentiment Analysis Explained
#crypto trading#crypto trading tips#Crypto trading bot+3 more tags

Trading 101: Sentiment Analysis Explained

Sentiment analysis is one of the three forms of analysis in your toolbox, next to technical analysis and fundamental analysis. Let’s learn how to use it!

The Details: Sentiment Analysis is a technology that helps you understand what people think and feel at a particular moment by analyzing opinions from various sources.

Drawing Analysis from Crowd Psychology

Thanks to recent advances in machine learning, we can now quickly and accurately understand and track sentiments in real-time. This means you can keep a close eye on what people are thinking and feeling.

Deep learning advancements alone didn't make sentiment analysis popular today. What really matters is the device you're using to read this blog post.

Now that over two-thirds of the world's population is online, you can find people's opinions on almost everything in comments, status updates, and headlines on your social media sites.

Twitter is especially great for getting the right data sets, making it a gold mine for researchers like you in this field.

Twitter has some important advantages.

Tweets are short, you can use hashtags to describe topics, and it's one of the quickest sources for breaking news. With AI, you can sort tweets based on positive, neutral, or negative sentiments.

This is incredibly valuable, especially in marketing and financial analysis. It helps you gain insights and predict buying behavior. Understanding sentiments makes market research more efficient and lets you spot trends as they happen.

Tweet Your Heart Out

Cryptocurrencies are closely tied to the internet and social media. Platforms like Twitter, Reddit, and Telegram are where tech-savvy crypto enthusiasts share information and thoughts.

In the cryptocurrency industry, public sentiment and valuation are closely connected. Social media posts discussing cryptocurrencies are prime candidates for deep learning analysis. This technology has shown how market sentiments are tied to price movements

Using Sentimental Analysis in Your Cryptocurrency Trading

To use sentiment analysis, you have three options.

Sentimental analysis copy bot

Our sentiment analysis copy bot employs advanced algorithms to gather data and send highly accurate signals tailored to each cryptocurrency we trade. You can use our copy bot for stress-free trading, eliminating the need to constantly develop your own algorithms.

Sentimental analysis indicators

You can choose from various sentiment indicators. One effective option is the 'Crypto Fear and Greed Index' available on simple websites. It considers factors like dominance, volatility, market momentum, and social media to provide valuable insights.”

Another option is subscribing to paid services, which offer more advanced machine learning algorithms. These services can analyze multiple social media platforms simultaneously for a more comprehensive sentiment analysis.

You can also gauge sentiments by examining data directly from cryptocurrency exchanges.

Two techniques you might find useful for your analysis are examining 'long versus short ratios' and monitoring 'margin rates'

When you look at the long versus short positions ratio of a cryptocurrency, you're essentially analyzing the percentage of market participants who are betting on the price to rise (going long) or fall (going short) at a specific time.

A general guideline for traders could be this: if around 60% of all investors on the exchange are looking to short a coin, it might suggest a bearish sentiment. In this case, the coin seems oversold, and an upward correction may be expected. Conversely, if most of the trades are long positions, the opposite could be true.

To gain a deeper understanding of how to interpret these percentage changes in various market conditions and identify the right moments for action, you can conduct further research. You can find information on long versus short ratios from sources like datamish or Bittrex.

Bulding a sentimental analysis bot

Building your own sentiment analysis bot is a challenging task.

First, you'll need programming skills, and Python is a great choice for automated trading due to its user-friendly nature and extensive libraries.

Next, you'll have to gather sentiment data from a social media platform, and Twitter has been a top choice over the years because of its comprehensive API.

Lastly, you'll have to write a script that can accurately interpret the data and generate suitable trading signals, similar to what we've done for our copy bot.

However, providing a detailed walkthrough of these steps is beyond the scope of this blog, which is meant to provide an overview of sentiment analysis. We may consider creating a future blog post that delves into the process in greater detail.


Sentiment analysis is a valuable tool to complement your technical and fundamental analysis.

However, it's important to note that relying solely on social media sentiment or studying buying and selling intent on exchanges may not always provide consistently reliable guidance for all your investment decisions.

Considering shifts in sentiments gives you valuable insights into the market and can enhance your confidence when identifying buying or selling opportunities, regardless of your trading style.

In the future, sentiment analysis accuracy is likely to improve as deep learning algorithms become better at analyzing online posts. Since cryptocurrency investors are heavily reliant on the internet, this knowledge can be a valuable asset.

We hope you found this blog helpful and now feel more confident about using sentiment analysis in your trading strategy. As always, happy trading!

Inbox Image


Get the weekly email with exclusive crypto analyses and news worth reading. Stay informed and entertained, for free.

Related Articles

Bot Trading 101 | How To Apply a Scalping Strategy
#Automated trading strategy#Strategy designer#EMA+3 more tags

Bot Trading 101 | How To Apply a Scalping Strategy

Cryptocurrencies | BTC vs. USDT As Quote Currency
#Bitcoin#crypto trading#crypto trading tips+2 more tags

Cryptocurrencies | BTC vs. USDT As Quote Currency

Technical Analysis 101 | What Are the 4 Types of Indicators?

Technical Analysis 101 | What Are the 4 Types of Indicators?

Bot Trading 101 | The 9 Best Trading Bot Tips of 2023
#crypto trading#trading bot#crypto trading tips+2 more tags

Bot Trading 101 | The 9 Best Trading Bot Tips of 2023

Start trading with Cryptohopper for free!

Free to use - no credit card required

Let's get started
Cryptohopper appCryptohopper app

Disclaimer: Cryptohopper is not a regulated entity. Cryptocurrency bot trading involves substantial risks, and past performance is not indicative of future results. The profits shown in product screenshots are for illustrative purposes and may be exaggerated. Only engage in bot trading if you possess sufficient knowledge or seek guidance from a qualified financial advisor. Under no circumstances shall Cryptohopper accept any liability to any person or entity for (a) any loss or damage, in whole or in part, caused by, arising out of, or in connection with transactions involving our software or (b) any direct, indirect, special, consequential, or incidental damages. Please note that the content available on the Cryptohopper social trading platform is generated by members of the Cryptohopper community and does not constitute advice or recommendations from Cryptohopper or on its behalf. Profits shown on the Markteplace are not indicative of future results. By using Cryptohopper's services, you acknowledge and accept the inherent risks involved in cryptocurrency trading and agree to hold Cryptohopper harmless from any liabilities or losses incurred. It is essential to review and understand our Terms of Service and Risk Disclosure Policy before using our software or engaging in any trading activities. Please consult legal and financial professionals for personalized advice based on your specific circumstances.

©2017 - 2024 Copyright by Cryptohopper™ - All rights reserved.