Social Analytics Platform LunarCrush Raises $5M in Series A Funding

LunarCrush, a social analytics and trading platform, today disclosed that it had raised $5 million in Series A funding, valuing the company at $30 million.
In an interview with Decrypt, co-founder and CEO of LunarCrush Joe Vezzani said, “It’s about building quality, long-lasting solid businesses, and not overextending yourself.” We reached a turning point where we felt the need to scale the crew up.

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Series by LunarCrush Draper Round Table and Ince Capital led a fundraising. Draper Associates, WWVentures, TRGC, Bitcoin Frontier Fund, Draper Goren Holm, Blockchain Founders Fund, Side Door Ventures, MoonPay, EMURGO, LBANK Labs, FUNFAIR Ventures, and Techstars were among the additional investors who participated in the round.

Launched in 2019, LunarCrush gathers data from the internet and social media platforms, such as Twitter, into a single dashboard and measures online sentiment using API and machine learning. LunarCrush recently added NFT and stock analysis to its cryptocurrency analysis capabilities.

According to Vezzani, the LunarCrush team is particularly interested in artificial intelligence and how it can affect Web3 as they explore for new ways to use the technology.

Vezzani stated, “We’ve used AI and machine learning from the beginning. We train [the AI] on various social media messages that were received for emotion, from bullish to pessimistic, concentrating on financials, using tools like Google TensorFlow and OpenAI’s ChatGPT.

A New Method for Predicting Market Trends

Investors’ positive or bearish views on an asset or the market are used to determine sentiment in the cryptocurrency and stock markets. “Bullish” refers to the conviction that an investment will appreciate, resulting in a favorable outlook. In contrast, the term “bearish” denotes a pessimistic viewpoint, the expectation of a decline in price, and a negative outlook.

The fact that the AI did not comprehend Web3 jargon was a challenge Vezzani claimed LunarCrush had to overcome when building AI models for cryptocurrencies and NFTs.

“If you posted, ‘I got wrecked on Dogecoin today,’ and you spelled it REKT; the natural language processing library doesn’t spell wrecked that way,” he explained. We needed to educate our system to recognize that as a negative sentiment, so to speak.

According to Vezzani, the additional funding will be used to grow the LunarCrush team and improve both the user experience and the scope of its analytical activities.

According to Vezzani, “We’re always trying to make use of the best technology at our disposal and provide the end user with a better experience than what is currently available.”