Utilizes vader lexicon sentiment analysis to identify major trends and engagement of Donald Trump's Tweets.
-
Updated
Nov 20, 2018 - Jupyter Notebook
Utilizes vader lexicon sentiment analysis to identify major trends and engagement of Donald Trump's Tweets.
Text mining using tweets of three politicians from RJ.
Sentiment analysis of tweets using machine learning
Implementation of the method TSTE for detecting popular topics in tweet dataset. Models topic as a set of semantically connected words using topic graph. Based on paper M. Cataldi, L. Di Caro i C. Schifanella, „Emerging Topic Detection on Twitter based on Temporal and Social Terms Evaluation”.
Perform sentimental analysis on the Elon-musk tweets (Elon-musk.csv)
A machine-learning approach to predicting market fluctuations based on tweet classification in social media articles
Trump Tweets Sentiment Analysis. Third Assignment for Data Analytics course @unimib18/19.
Pequeña introducción a la captura de tweets y algo de data mining usando R
En esta práctica se empaqueta y distribuye una aplicación Python que descarga y analiza tweets en función de puntuaciones de sentimiento. Los resultados del análisis se guardan en una base de datos MongoDB, y la información se muestra en la web.
Social Media Sentiment Analysis
This project aims to built, test and select a Natural Language Processing model that has optimal performance to predict cyberbullying type of tweets from an account
Final project for "Natural Language Processing" course at University of Tartu. December 2017.
Data analysis platform that guides you in the creation of digital content and facilitates the development of marketing strategies.
Determining the correlation between the market value of company respect to the public opinion of that company. And to answer the question that "Does tweet volume have any effect on stock market trading volume?"
Exploring Public Opinion Dynamics From 2020 U.S. Election Tweets, CSC440 Fall 2023
Dexter is a friendly bot powered by a multichannel convolutional neural network 🤖
Pipeline used to analyze tweets using text mining and graph mining approaches
Implementation of the method Trend Miner for detecting popular topics in tweet dataset. Models topic as a set of semantically connected words using word cooccurrences. Based on paper N. Pervin, F. Fang, A. Datta, K. Dutta i D. Vandermeer, „Fast, scalable, and context-sensitive detection of trending topics in microblog post streams”.
CoviSA is a Visualization Dashboard for analyzing the Sentiments and Emotions related to COVID-19 Tweets.The project fetched data from Twitter and analysed it using a ML Model. The web app is developed with ReactJS served over a Flask server.
Add a description, image, and links to the tweet-analysis topic page so that developers can more easily learn about it.
To associate your repository with the tweet-analysis topic, visit your repo's landing page and select "manage topics."