Data analysis of tweets about a controversial situation of a YouTuber. Used TwitterAPI to fetch tweets and performed sentiment analysis
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Updated
May 12, 2019 - Jupyter Notebook
Data analysis of tweets about a controversial situation of a YouTuber. Used TwitterAPI to fetch tweets and performed sentiment analysis
M.Tech (Software Engineering) Sep 2016 - Final Dissertation Project
This program do sentimental analysis on given hashtag and give output as if its positive sentiment or negative sentiment.
Twitter Sentiment Analysis using machine learning models.
Scrapped and Analyzed Twitter data using Spark. Run Spark queries on Millions of tweets and trained models for sentiment analysis.
Experiments in the field of Sentiment Analysis using ML Algorithms namely Logistic Regression, Naive Bayes along with tfidf, one hot encoding, bag of words vectorization. Different MLP and RNN models viz. LSTM, GRU, Bidirectional LSTM. Lastly, state of the art BERT model
Given Dataset:-
MSP Penn Data Analysis Workshop - February 2018
Sentiment Analysis is a technique used in text mining. Twitter Sentiment Analysis may, therefore, be described as a text mining technique for analyzing the underlying sentiment of a text message, i.e., a tweet. Twitter sentiment or opinion expressed through it may be positive, negative or neutral.
US Election, in particular, analysis of Biden and Trump's use of Twitter
Sentiment Analysis Dashboard Using Tableau
sentiment analysis nlpcore
Using NetworkX for Social network analysis
This research wants to build a time serie of the polarity of tweets related to a cluster of firms, and compare it to the time serie of the same firms in the stock market.
Identified Tweet sentiment towards tech companies to assess investment opportunities
Twitter Sentiment Analysis using Machine Learning and Data Analysis with Python
twitter real-time sentiment analysis
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