Crypto Sentiment Analysis via StockGeist.ai

Crypto sentiment is defined as the crowd psychology towards the cryptocurrency market. Traders and investors can utlilize crypto sentiment analysis as an important factor in predetermining price movements.

The World of Cryptocurrency

The first crypto established was Bitcoin, founded in 2009, and is still to this day regarded as the best known crypto. Traders of tokens, such as Bitcoin, can make short term investments due to the volatility of the market or “hold” in the hope that over a long period of time the value skyrockets.

The volatile nature of this digital market plays a key role in what makes it so interesting and appealing for traders. Online speculation can result in prices increasing tenfold or taking a sharp dive. This is what makes crypto sentiment analysis such a key factor in helping predict any forthcoming price shift.

What role does StockGeist.ai play in crypto sentiment analysis?

StockGeist.ai is an interactive platform that provides real time crypto market sentiment analysis for over 350 different coins. This list is continuously growing as our custom built tools scrape the top 100 list on a daily basis and any previously unlisted coins on our platform are permanently added for users to analyze. 

The crypto sentiment data is derived from textual messages across social media platforms. This simplifies the process for traders which would otherwise require a manual, time-consuming browse of different socials to discover the perceived crowd psychology towards a particular token. Given the popularity of cryptocurrency, hundreds or even thousands of messages are likely to be posted every minute making it a difficult and trivial task to keep track of. 

StockGeist.ai’s ingenious platform is powered by AI deep learning-based solutions to be able to depict the real time crypto sentiment data with just a few clicks. Crypto sentiment analysis via StockGeist.ai is reported in various ways including the following:

Crypto Sentiment

Users are able to view the crypto market sentiment analysis of individual digital currencies based upon the distribution of positive/negative/neutral sentiment. Messages are placed into two classes, being either informative or emotional. For example, a message such as “To the Moon!” would be considered as highly emotional, whilst “X reported an overnight drop of 12% in value” would be classed as informative.

News

News articles revealing new developments surrounding the world of cryptocurrency or related to a specific digital currency are constantly being released from various publications all across the world. We locate relevant news articles for each listed digital currency on our platform and label them by sentiment accordingly. This provides the reader with a fast way to access all news stories and highlights any crypto sentiment throughout.

Ranking

We create rankings of all the top trending cryptos based upon all of the data gathered by our crypto market sentiment tool, namely the number of messages. Users are able to view changes in dynamics of each rank, as well as the user can explore the data across different timeframes (last 5 minutes, last hour and last day).

Upcoming Crypto Sentiment features

WordCloud

WordCloud is a completely unfiltered group of words or topics that are most prevalent amongst social media platforms at that current time. No filters are applied to this tool so it is the fastest way to grasp the crypto sentiment of the masses with just one click.

Watchlist

Users are able to create a shortlist of cryptocurrencies that they are interested in. These can be freely customized and updated with new cryptos as the user desires. StockGeist.ai displays the rank change along with sentiment. Additionally, cryptos on the watchlist can be analyzed using a number of graphs in the Watchlist Charts section to provide further detailed crypto sentiment analysis.

 The importance of crypto market sentiment analysis

Crypto sentiment analysis should be an integral tool to any trader and investor for deciding whether the time is right for investment or selling a commodity. Although, crypto market sentiment analysis should be used in conjunction with other methods of analyzing market trends of digital currencies such as: 

  1. Analyzing a token’s whitepaper - The whitepaper contains the main aims of the projects and use cases for that token. Investors and traders alike will try to ascertain whether the outlined goals are realistic and achievable, as well as ensuring the whitepaper is not similar to an existing token.
  2. What major problem is the token solving? Determining the solution a particular token is providing will help highlight the utility value of a token’s market value. For example, blockchain projects that uniquely solve a major problem will have a higher demand, therefore elevating the tradable value of the token.
  3. Projects social media following - Discover how the team is running each of their social media profiles. A good token will successfully be gaining popularity or noise amongst a huge following and capatilizing on viral opportunities that present themselves. This will also inform you more about the project to make informed decisions.
  4. Previous price history - Can you spot any trends in the price shifts over time and can these be linked to any specific events which may or may not occur again? An extremely volatile price value will either put traders and investors off, or provide an opportunity for experienced traders to take advantage of any future price shifts which appear to mirror previous movement.
  5. Team behind the project - You want to back a token that is being supported by a group of funders who believe wholeheartedly in the project. The fundamental analysis of the team members is important to determine whether the token is in capable hands. Traders may investigate whether they have worked on related projects in the past? Are they members of the blockchain ecosystem? Qualifications?

Get started with your crypto market sentiment analysis today courtesy of the StockGeist.ai platform so you can increase the accuracy of your trading decisions. Users can also integrate our crypto sentiment API into their own projects ably through various programming languages. 

Crypto analysis tools and case studies

Crypto analysis tools and case studies are critical for understanding the behavior and performance of cryptocurrencies in the market. These tools use various metrics such as trading volume, price trends, and market cap to analyze the movement of cryptocurrencies and their underlying blockchain networks. Some popular tools used for crypto analysis include CoinMarketCap, TradingView, and CryptoCompare. These tools allow users to track the price of different cryptocurrencies and compare their performance against each other. Additionally, case studies provide valuable insights into the behavior of cryptocurrencies in specific market conditions and scenarios. By studying these cases, investors can gain a better understanding of the factors that drive cryptocurrency prices and make more informed investment decisions. Overall, crypto analysis tools and case studies play a critical role in understanding the complex and dynamic world of cryptocurrency trading.

Bitcoin sentiment analysis

Bitcoin sentiment analysis is the process of using natural language processing (NLP) and machine learning techniques to analyze and interpret the emotional tone and attitudes expressed towards Bitcoin in online conversations and social media posts. It involves collecting data from various sources such as social media platforms, news articles, forums, and blogs to gain insights into how people feel about Bitcoin. By analyzing the sentiment of these conversations, businesses and investors can make more informed decisions about buying or selling Bitcoin. Bitcoin sentiment analysis can also help predict market trends and fluctuations, allowing traders to take advantage of market opportunities. However, it's important to note that sentiment analysis is not foolproof and can be influenced by factors such as fake news, manipulation, and bias, which can lead to inaccurate results.