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It used to take days for financial news to spread via radio, newspapers, and word of mouth. Now, in the age of the internet, it takes seconds. Did you know news articles are automatically being generated from figures and earnings call streams? In this project, I generated investing insight by applying sentiment analysis on financial news headlines

Home Page: https://barionleg.github.io/Extract_Stock_Sentiment_From_News_Headline/datasets/fb_05ene.html

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extract_stock_sentiment_from_news_headline's Introduction

Extract_Stock_Sentiment_From_News_Headline

It used to take days for financial news to spread via radio, newspapers, and word of mouth. Now, in the age of the internet, it takes seconds. Did you know news articles are automatically being generated from figures and earnings call streams? In this project, I generated investing insight by applying sentiment analysis on financial news headlines from Finviz. Using this natural language processing technique, I have also understood the emotion behind the headlines and predict whether the market feels good or bad about a stock. The datasets used in this project are raw HTML files for the Facebook (FB) and Tesla (TSLA) stocks from FINVIZ.com, a popular website dedicated to stock information and news.

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