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.DS_Store (6148, 2021-03-04)
.ipynb_checkpoints (0, 2021-03-04)
.ipynb_checkpoints\crypto_sentiment-checkpoint.ipynb (964537, 2021-03-04)
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Images\btc.png (36323, 2021-03-04)
Images\btc_wc.png (1202340, 2021-03-04)
Images\eth.png (35212, 2021-03-04)
Images\eth_wc.png (1187285, 2021-03-04)
crypto_sentiment.ipynb (964537, 2021-03-04)

# Sentiment Analysis for Cryptocurrencies In this assignment, I was asked to apply natural language processing to understand the sentiment in the latest news articles featuring Bitcoin and Ethereum. Moreover, I had to understand the other factors involved with the coin prices such as common words and phrases, organizations, and entities mentioned in the articles by using the following techniques: 1. [Sentiment Analysis](https://github.com/padthai-sketch/Crypto-Sentiment-Analysis/blob/master/#Sentiment-Analysis) 2. [Natural Language Processing](https://github.com/padthai-sketch/Crypto-Sentiment-Analysis/blob/master/#Natural-Language-Processing) 3. [Named Entity Recognition](https://github.com/padthai-sketch/Crypto-Sentiment-Analysis/blob/master/#Named-Entity-Recognition)   #### **The Sentiment Analysis of Bitcoin and Ethereum News indicates that Bitcoin outperformed Ethereum by having the highest average score at 0.051. Moreover, it also receives a higher positive score and compound score. Below are the Word Cloud representing the keywords that frequently appeared in the latest articles of these cryptocurrencies.**  

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