Sentiment

Sentiment πŸ“ˆ

The Sentiment endpoint collects data from Twitter, Reddit, and all the Crypto News. It analyzes the discussions surrounding the whole crypto market to determine the sentiment or attitude expressed towards the industry. Sentiment is determined by calculating a polarity score, ranging from -1 (Very Negative) to 1 (Very Positive), for each social platform. The overall sentiment is then determined by taking a weighted average of the polarity scores across all three platforms and assigning a sentiment label based on the result.

The sentiment endpoint is updated every hour.

Datapoints:


DATETIME

The date and time of calculation of sentiment.


MARKET_SENTIMENT_GRADE

Sentiment grade for the whole crypto industry across all medium.


MARKET_SENTIMENT_LABEL

Sentiment label for the whole crypto industry, such as "positive" or "negative".


NEWS_SENTIMENT_GRADE

Sentiment grade for the crypto industry across the news.


NEWS_SENTIMENT_LABEL

Provides a descriptive label for the news sentiment grade, such as "positive" or "negative".


NEWS_SUMMARY

Provides a brief summary of the latest news related to crypto.


REDDIT_SENTIMENT_GRADE

Sentiment grade for the crypto industry across Reddit.


REDDIT_SENTIMENT_LABEL

Provides a descriptive label for the Reddit sentiment grade.


REDDIT_SUMMARY

Provides a brief summary of the latest Reddit discussions related to crypto.


TWITTER_SENTIMENT_GRADE

Sentiment grade for the crypto industry across Twitter.


TWITTER_SENTIMENT_LABEL

Provides a descriptive label for the Twitter sentiment grade.


TWITTER_SUMMARY

Provides a brief summary of the latest Twitter discussions related to crypto.


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Visualize on Token Metrics Application:

Go to the Sentiment Analysis tab. This is where we showcase our TM Sentiment Analysis.

Screenshot from Token Metrics Application: Tokens sorted by Sentiment from High to Low.

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Example Use Case:

The Sentiment Analysis feature in the Token Metrics Data API helps traders keep track of market sentiment and make informed trading decisions. Traders can use this data to identify positive or negative sentiment around a specific token, which can help inform their buying or selling decisions. For example, if the sentiment analysis indicates a high level of positive sentiment for a token, the trader may decide to buy or hold the asset, hoping for a potential price increase. Conversely, if the sentiment analysis shows a high level of negative sentiment, the trader may decide to sell or short the asset, anticipating a potential price decrease.

In addition, the Sentiment Analysis can also help traders identify trends and patterns in market sentiment, which can inform their overall trading strategy. For instance, if the sentiment analysis indicates a high level of positive sentiment for a particular project or protocol, the trader may choose to concentrate their investments in that token or sector.