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Created a Python script to perform a sentiment analysis of the Twitter activity of various news outlets. These findings are visualized in both a scatter plot and a bar chart. Skills Needed: Python, Pandas Library, Jupyter Notebook, Tweepy, TextBlob Matplotlib and Seaborn
Wrangling and analysis of Tweets from WeRateDogs (@dogrates) with Python in Jupyter Notebook. Project focuses on gathering, assessing and cleaning data. Various methods, including Python's Requests and Tweepy packages for performing a GET Request and querying Twitter API, were used to collect Tweets and relevant data available online.
Sentiment Analysis application for the presidential elections Ecuador 2021 using Twitter API. Also a text classification model with SVM, Naive Bayes and Random Fores made in python notebook. University of Cuenca Text Mining course 🎓
This repository explains the code for collecting the data from Twitter API. The code is saved in Jupiter notebooks, follow the guideline in the README file.