fischlerben/Natural-Language-Processing-Crypto
Sentiment Analysis surrounding Bitcoin & Ethereum utilizing Python Natural Language Processing (NLP) techniques.
This project helps cryptocurrency investors and analysts understand public sentiment around Bitcoin and Ethereum by analyzing news articles. It takes recent headlines and article content as input and outputs sentiment scores (positive, negative, neutral, compound), word frequency counts, word clouds, and identified key entities (like organizations or currencies) from the text. Anyone tracking cryptocurrency market sentiment for investment or research would find this useful.
No commits in the last 6 months.
Use this if you want to quickly grasp the prevailing mood and key topics in news coverage for Bitcoin and Ethereum.
Not ideal if you need to analyze sentiment for a wide range of cryptocurrencies beyond Bitcoin and Ethereum or require real-time sentiment tracking.
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Jan 24, 2021
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