This guide will introduce you to sentiment analysis, some tools for tracking sentiment and some tips for incorporating these techniques into your trading.
Read our guides on fundamental analysis and technical analysis if you haven’t done so already!
Overview
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What is Sentiment Analysis?
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Google Trends
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Gauging Sentiment Using Twitter
- Case study: Elon Musk and Dogecoin
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Dune Analytics
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LunarCrush
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Santiment’s Social Volume
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Implied Volatility and the Put-Call Ratio
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Pros and Cons of Sentiment Analysis
What is Sentiment Analysis?
Sentiment analysis is concerned with understanding the general public’s attitude towards a cryptocurrency. The overall emotion of market participants can drive price action, where the emotions of euphoria and greed are associated with late stages of bullish market cycles, while depression and fear characterize the final stages of bearish market cycles.
Source: Forbes
With the rising popularity of social media platforms like Reddit and Twitter, traders can gauge what people are feeling or thinking by analyzing the phrases used and the tone of tweets or other social media posts.
The sentiment approach to trading has been utilized by hedge funds and other market participants seeking to capitalize on the wealth of social data that is generated every day through platforms like Reddit and Twitter. Many investors use computer models incorporating social signals, which is also used in traditional financial markets, making use of natural language processing to identify key words and emotions to capture the current sentiment.
While sentiment can drive markets over short time periods, relying on this technique alone is not recommended, as fundamental or technical factors may outweigh positive or negative sentiment. Nevertheless, spotting projects with improving sentiment can be profitable, as we’ll see later on in this article.
Google Trends
Research has shown that the number of Google searches for Bitcoin and Ethereum are strongly correlated with price. This is illustrated nicely by The Block’s data dashboard that tracks Google Trends data.
One technique to make Google Trend data actionable is explained by AlgoHive founder Marc Howard, where he takes the data for “BTC-USD” and “Buy Bitcoin” over a 90-day period and buys bitcoin whenever the ratio between these two terms is less than 35%.
For example, if the number of searches over a 90-day period for “BTC-USD” is 350,000 and is 80,000 for “Buy Bitcoin”, then you’d buy or go long, as the next day the price tends to increase. However, when the ratio between “BTC-USD” and “Buy Bitcoin” is above 35%, it is taken as a sell signal.
Gauging Sentiment on Twitter
A simple search of a token’s ticker on Twitter can help you to get a feel for the current sentiment. However, the search results may also include spam posts, pump and dump groups and so on, so there are some more sophisticated methods to use Twitter to gauge sentiment and find actionable trading signals.
One method is to use the number of new Twitter followers for established brands such as Binance and CoinMarketCap as a proxy for interest in the cryptocurrency market, which can be tracked from The Block’s data dashboard.
When these accounts gain a lot of new followers, it seems to shadow price movements in the crypto market. In bull markets, we can see rapid growth but during bear markets, the number of new followers declines rapidly as people lose interest. Notice how the peaks of the new followers align with the peaks in market valuations.
If you’re trading based on sentiment, then it’s essential to use the notifications feature for important Twitter accounts. For example, accounts with a large number of followers are more likely to have an impact on the market, so you might want to be notified each time these influencers tweet to spot potential opportunities. Also, trending news stories can have an impact on how market participants feel, so it’s a good idea to closely track breaking news stories through Twitter.
For example, @tier10k is a popular account that tweets cryptocurrency-related breaking news. Given that big news stories can have an impact on sentiment, it can be profitable to simply trade the headlines based on the sentiment it conveys.
The chart below illustrates a negative impact on the price of APE when @tier10k tweeted negative news about the Bored Ape creator facing an SEC probe. The negative development pushed the price of Apecoin down by more than 17% in the following couple of days as sentiment started to sour.
Another feature worth using is Twitter’s lists feature. Whether it’s finding alpha, seeing what traders and investors are talking about or for gauging the sentiment within different cryptocurrency communities, lists are an efficient way of tracking what’s going on, what people are focusing on and how they feel about a particular token.
*Whale watching is another method for sentiment analysis, which is covered in more detail in our blog post. *
Case Study: Elon Musk and Dogecoin
As one of the richest people in the world and with over 100 million Twitter followers, Elon Musk is a prime example of how an influential individual can impact sentiment and move markets.
The chart below overlays his tweets that were positive in sentiment with the price of DOGE and highlights what is known as the ‘Elon effect’, where his tweets often sparked large price movements in Dogecoin. Other traders and investors bought DOGE on the back of his comments and improved market sentiment as the altcoin gained more attention.
Source: TradingView
Dune Analytics
Searching Dune Analytics for trending dashboards gives us a sense of what market participants are focusing on. You can track the trending dashboards on a regular basis to keep a pulse on what cryptocurrency investors are interested in. Below we can see the current flavor of the day is Reddit NFTs, judging by the number of trending dashboards in the past 24 hours.
A similar technique can be used for CoinGecko and CoinMarketCap to monitor trending assets. But the idea here is not to blindly short or long assets that are trending. Instead, you should use these methods to filter which assets to pay attention to.
LunarCrush
LunarCrush is a suite of sentiment analysis tools that are available for free, but more insights can be gleaned by HODLing their native LUNR token to unlock more features. For the basic plan, you can track social mentions, cryptocurrency influencers and set up customizable alerts based on price, volume, and social metrics.
Given Bitcoin and Ethereum are the largest and most popular cryptocurrencies, it’s not surprising that they generate the greatest number of social mentions and engagements. However, when you notice that a cryptocurrency is closing in on Bitcoin and Ethereum in social mentions or engagements, then it indicates that sentiment is very strong.
An example is shown below, with APT recently matching Ethereum in the number of social mentions.
When Elon Musk was tweeting about Dogecoin a lot, Dogecoin showed a similar dynamic becoming the third most mentioned cryptocurrency on social media.
What is particularly interesting about LunarCrush are their proprietary sentiment indicators: the AltRank and Galaxy Score, which are combined to find the “Coin of the Day”.
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AltRank: a score given to cryptocurrencies that tracks market volume rank, social volume rank, percentage change versus Bitcoin and social score rank. If a cryptocurrency is consistently achieving a high rank, then it’s worth looking deeper into it and finding potential opportunities.
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Galaxy Score: this score is measuring a cryptocurrency against itself with respect to community metrics pulled in from across the web, indicating how well a coin is performing. The metric is made up of four indicators: price, social sentiment, social impact and how strongly social data and price/volume are correlated.
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Coin of the Day: The coin of the day is selected at 00:00 UTC every day combining the previous days’ AltRank and Galaxy Score to find the asset with the highest weighted average, indicating strong positive sentiment.
Santiment’s Social Volume
Santiment’s social volume indicator is a proprietary metric pulling sentiment data from BitcoinTalk, Twitter, Reddit and Telegram for different cryptocurrencies to determine how investors and traders are feeling about an asset.
Rising social volume indicates improving sentiment while declines suggest people are losing interest. However, this metric is not available under the free plan, but we do track it for the markets available on Perp v2 in our monthly reports.
Another cool feature of Santiment is the social tool showing trends over the past 24 hours, which is useful if you want to catch up on the biggest trending topics or have been out of the loop for a while.
Finally, the insights feature allows traders to share their thoughts on the markets using Santiment data, which may help you to spot promising opportunities to short or long an asset as well as give you more ideas on how to use sentiment analysis in your trading.
Implied Volatility and the Put-Call Ratio
As well as what people are saying, sentiment analysis also includes working out what people are actually doing. To gauge how sophisticated investors are feeling and how they are positioning themselves in the market, we can look at two metrics related to options: implied volatility and the Put-Call ratio.
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Implied volatility can be interpreted as a measure of fear amongst investors. Implied volatility usually increases in bear markets and decreases in bullish markets. The implied volatility for Bitcoin and Ethereum can be tracked here.
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The Put-Call Ratio tells us the balance between the number of put options (bearish) and number of call options (bullish) that are traded. If the ratio is below 1, then sophisticated investors are suggested to be bearish. However, if the ratio is above 1, then more call options have been traded (which suggests bullish sentiment) as compared to put options. The Put-Call ratio for Bitcoin and Ethereum can be tracked on The Block’s data dashboard.
Pros and Cons of Sentiment Analysis
Pros
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Sentiment is arguably a more significant driver of cryptocurrency prices as compared to traditional financial markets as fundamentals are not as well defined when compared to equities or foreign exchange markets.
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Sentiment analysis works better with mid- and small-cap cryptocurrencies, as for large-caps like Bitcoin and Ethereum, improved sentiment alone is not enough to move these highly liquid markets.
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Often sentiment can be a leading indicator since it represents where people think the market will go next. Unlike a lot of technical tools used by chartists and fundamental data that is backward looking, sentiment analysis is mostly forward looking.
Cons
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Sentiment can change very quickly so this form of analysis has little use for taking long-term positions in the market. It is also not useful on its own and should be supplemented with technical and fundamental analysis, especially over longer timeframes.
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Increased social volume may be associated with pump-and-dump schemes instead of a genuine improvement in sentiment. You’ll have to determine whether aggressive buying or selling (which is what moves market prices) was precipitated by some social event or if the sentiment we see on social media is simply a reaction to aggressors who are buying or selling.
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Algorithms that are proprietary do not reveal their methods and are not transparent. Sentiment tools can also be influenced by a large number of off-topic and spam social media posts, or malicious actors who use multiple accounts to engage in social engineering.