From the TSLA surge of 2020 to the infamous Reddit vs Wall Street battle of GME, there have been multiple occasions of stock sentiment tools correctly forecasting price movements. Here are three of the most notorious.
1. Tesla (TSLA) – The Twitter (X) Surge of 2020
Long before Twitter became X and part of Musk’s empire, it was the cauldron for an explosion in the stock price of TSLA during 2020. Whilst traditional analysts were divided over the stock, NLP-powered stock sentiment platforms were picking up overwhelmingly positive mentions across Twitter (X) and Reddit.
Tesla’s stock soared more than 300% between March and August 2020, from a split-adjusted close of $72.24 on March 18th to $498.32 on August 31st – although it is important to note that Tesla performed a 5-for-1 split in August – but this still left an adjusted price of $99.66.
In a 2024 paper, Jayanthi and Parr found a strong correlation (r = 0.68) between the positive sentiment and Tesla’s stock price in 2020. Sentiment data correctly identified the bullish attitudes of retail investors before the upward price movements.
The link between Tesla stock and sentiment data is well researched in academia. A 2022 study by Bhadkamar and Bhattacharya confirmed that an increased volume of Elon Musk’s tweets often led to higher close prices, and vice versa.
For retail-heavy stocks, stock sentiment analysis can reveal early bullish or bearish trends.
2. GameStop (GME) – When Reddit took on Wall Street
If ever you needed proof of the power of social media in determining stock prices, the GameStop stock price is all the evidence you will ever need.
Whilst it was seemingly all of r/WallStreetBets that came together to rally around the GME stock, it was u/DeepFuckingValue, also known on YouTube as Roaring Kitty, who led the charge.
Starting as early as 2019, DFV started raising awareness of the supposed undervaluation of the GameStop stock, which as of 2019 was trading at $4/share.
His posts on r/wallstreetbets showed other traders that the stock had a high short interest, at over 100% of the float on occasion. This made a short squeeze mathematically possible, if enough people were on board.
It is fair to say that DFV’s posts didn’t just inform other traders, they sparked a movement, the likes had never been seen before and are unlikely to be repeated.
In late 2020, DFV’s positions started to gain traction on Reddit. It was in January 2021 that the media coverage began, with the posts starting to go viral. From January 21st to 28th, GME skyrocketed from ~$40 to ~$483 intraday.
The effects of this movement were legendary. Many ‘average joe’ traders successfully gambled on the price increase, entrenching the meme stock era as a force to be reckoned with.
Regarding the sentiment analysis of GME, a surge in subreddit activity often closely preceded price spikes, with positive sentiment posts strongly correlated with intraday and interday price increases. Volume and engagement metrics, such as upvotes and comments, were leading indicators of the price volatility that was to follow. It was the first time that a coordinated social media campaign influenced retail sentiment enough to significantly move a public stock price.
GME is seen as the ‘posterchild’ of the sentiment success stories because not only was DFV’s underlying core thesis about the stock being undervalued proved to be fundamentally sound, there was a mass sentiment amplification across Reddit, Twitter (X) and YouTube. The high short interest triggered a feedback loop of forced buying, which ramped up the price using short squeeze mechanics. The resulting price increase forever changed how Wall Street viewed retail sentiment.
3. Moderna (MRNA) – Covid Vaccine Sentiment
Cast your mind back to the Covid-19 pandemic, Moderna were amongst the most-discussed companies in the world. They were responsible for one of the first Covid-19 vaccines to be approved in the world. The sentiment analysis of the Moderna stock is amongst some of the clearest examples of the relationship between public sentiment, news stories and media framing can influence stock prices.
Moderna Sentiment Timeline
May 18th 2020
Phase 1 trial results for the Moderna mRNA-1273 vaccine were released, with global headlines praising the “promising results”. What followed was a 20% intraday stock price increase, hitting an all time high for MRNA.
May 19th 2020
Just a day later, a prominent article in STAT News questioned the robustness of the phase one trial data, leading to a flip in media sentiment regarding MRNA. The stock price dropped 10% that day alone.
December 18th 2020
The FDA approved the Moderna vaccine for emergency use, resulting in a peak of public and institutional optimism in the MRNA stock, with a ~5% price rise resulting in a new all time high.
The role of sentiment
NLP analysis of sentiment of posts within r/stocks and r/wallstreetbets showed a close correlation ( r > 0.6 ) between the positive versus negative sentiment score and the daily closing price. Using historic sentiment data from the StockGeist.ai platform, a sharp positive tone shift on December 17th and 18th preceded a 5% rise in the stock price the following trading day.
A 2021 Study published in the Journal of Computational Social Science stated that “COVID-19 vaccine stocks such as Moderna and Pfizer exhibited a unique volatility pattern highly correlated with Twitter (X) sentiment metrics and media coverage density”.
The findings attribute circa 25% of the intraday return variance on biotech stocks during the trial announcements to social media sentiment swings. Sentiment was proving not just to be a reaction, but instead it both anticipated and helped to magnify price action.
Incorporating stock sentiment into your trading strategies
StockGeist is the place to find real-time stock sentiment data. Whether you are looking for an easy-to-use platform to find stock sentiment data, or an API that can supply the sentiment data feed to integrate seamlessly into your trading dashboard, StockGeist is here to help.
NLP Team Lead at Neurotechnology | StockGeist Project Lead – Senior NLP & LLM Developer
Vytas is a figurehead at Neurotechnology – founder and NLP team lead of StockGeist.ai at the age of just 21. With over 7+ years of experience in LLM and NLP development, Vytas’ passion and knowledge for developing AI-powered solutions burns brighter than ever before. He has a vast amount of experience in the field of sentiment analysis for the stock and crypto market, helping traders and investors better understand textual data across social platforms through his innovative platform, StockGeist.ai.
