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Developed a Python program that scrapes tweets off Twitter using twint, based on the user’s input and exports the data as CSV. Extracted and analyzed sentiments using Afinn to examine how positive or negative the tweets are, using Matplotlib to display them on a pie chart.+more
The goal of this project was build recommender systems using K-means and ALS based on the average ratings. It recommends similar books, recommends author based on a book title, recommends high rated books of the author.
Experiments with web crawling, scraping, and indexing a collection of web documents. Clustering the indexed data with k-means algorithm. Each resulting cluster is assigned a sentiment score using AFINN - a sentiment analysis script.
The objective of the project is to detect the underlying sentiments of the product reviews. Classifying the reviews as positive, negative and neutral helps to determine the overall emotion behind the product and assist business strategies.
This work is a text analysis in R based on the NASA data found in: https://data.nasa.gov/data.json . The text analysis is based in different steps starting with lexicons. Further investigating positive and negative sentiments on a world cloud . Also, correlations between words are analysed.
A web scraping and sentiment data analysis of 707 Star Trek episodes, including The Original Series, The Animated Series, The Next Generation, Deep Space Nine, Voyager, and Enterprise.