https://towardsdatascience.com/useful-sentiment-analysis-mining-sec-filings-part-1-358942fc98ed > Ugh. Sentiment Analysis. To be honest, I roll my eyes every time I hear about the use of sentiment analysis for trading stocks. It’s not that it doesn’t work, it’s that most of the products I’ve come by in my professional capacity (data science/research for trade idea generation at a fund) have been gimmicky: tracking tweets, parsing news headlines, parsing earnings statements after release, parsing Fed notes…the list goes on and on and on. These products have had varying efficacy and large price tags. Without naming names, a recent product which analyzes tweets incorrectly tagged twitter memes and jokes about Red Dead Redemption 2’s many bugs as an “insight” that unit sales were weak. They were Red Dead Wrong, now focusing on Redemption — and I can keep making these puns all day. > So, what’s the purpose of this piece and why I am looking at sentiment analysis if my sentiment on it is so negative to begin with? Well, textual data has a lot of power. One of the interesting things with modeling and forecasting is that data mass (the amount of data you are working with) has more impact than algorithmic complexity.