Keeping abreast of cryptocurrencies means frequently browsing and interpreting vast amounts of content from various online sources. As the crypto markets expands and matures, information overload becomes a problem. Astute traders are increasingly seeking crypto-specific tools that can distill the noisy input data into quality insights. Predicoin is one such potential solution.
Predicoin Goes Live With “Sentscore” Functionality
In August, news.Bitcoin.com previewed Predicoin, which was then in early stage development. The data analytics platform, which is now open to the public, aggregates news and social media content before extracting the sentiment using machine learning. In addition to serving up crypto news and social media content, Predicoin provides its own built-in analytics in the form of “Sentscore” (sentiment score). This functions as a general sentiment indicator for the cryptomarket, powered by algorithms that compute sentiment from five verticals:
- Amount of content and article context from crypto news sites
- Social media sentiment (currently Twitter and Reddit) and volume from crypto influencers
- Macro and micro economics/fundamentals of a coin (team, developers etc.)
- Technical indicators on a coin’s price
- Popularity and trending characteristics of a coin
Predicoin plans to use its datasets and analytics framework to derive trends between sentiment and price. “We’re still tuning our algorithms and regularly backpropagating updates to prior data,” explained Pierre-Alexandre Picard, Predicoin COO. “These metrics could change, but we’re very excited to start seeing some potential correlations on our charts. We continue to work hard on identifying patterns to provide the most accurate indicators to our users.”
Gauging Social Sentiment
Although Predicoin is still in beta, testing shows the platform to be quite efficient in some cases at accurately conveying social trends. For instance, at the height of the recent Bitcoin Cash fork, Predicoin detected a significant upward shift in volume of news and social media that mentioned BCH. While this finding isn’t surprising, seeing the data overlaid with that of BCH price action suggests the degree to which sentiment can be used to predict price.
This is best seen in the case of Ripple’s eponymous cryptocurrency. XRP’s price run-up in September, which was linked to the announcement of U.S.-based PNC Bank partnering with Ripple to conduct instantaneous cross-border payments. Predicoin identified the positive news published on XRP and shared multiple times across social media, taking its native Sentscore to an all-time high for ripple. The price followed within the next 12-24 hours, boosting XRP to over $0.60.
BTC’s social chart is also interesting to explore, showing sentiment falling with the bitcoin crash that occurred on Nov. 15:
The platform detected a strong downturn in the sentiment of social media the moment BTC lost around $100. To further improve its algorithmic predictions, Predicoin runs statistical tests on the data it amasses to develop metrics that connect price and social information. The goal is to ultimately develop a tool that traders and investors can rely on for asset research.
Predicoin’s data analytics service currently extends to 30 cryptocurrencies, enabling enthusiasts to log in and discover social patterns, check daily, weekly, and monthly scores, and access the content from which these scores are formulated. Generating profit in a bear market isn’t easy, even when armed with tools and algorithms aplenty. Given the fallibility of technical analysis, however, alternative indicators are to be welcomed, be it to bolster existing trading ideas or to give rise to new ones.
Do you think sentiment analysis can be a valuable trading indicator? Let us know in the comments section below.
Images courtesy of Shutterstock and Predicoin.
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