sharmaroshan / Twitter-Sentiment-Analysis

It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization

Date Created 2019-03-31 (5 years ago)

Commits 10 (last one 5 years ago)

Stargazers 234 (0 this week)

Watchers 4 (0 this week)

Forks 120

License gpl-3.0

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RepositoryStats indexes 589,134 repositories, of these sharmaroshan/Twitter-Sentiment-Analysis is ranked #160,573 (73rd percentile) for total stargazers, and #374,926 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #3,636/17,281.

sharmaroshan/Twitter-Sentiment-Analysis is also tagged with popular topics, for these it's ranked: machine-learning (#3,057/7978), nlp (#902/2415), data-visualization (#391/910), data-analysis (#272/662), classification (#177/541), sentiment-analysis (#80/248), eda (#51/140)

Other Information

sharmaroshan/Twitter-Sentiment-Analysis has Github issues enabled, there are 4 open issues and 0 closed issues.

All Topics

eda nlp hashtags wordcloud bag-of-words datacleaning data-analysis classification count-vectorizer cross-validation machine-learning data-visualization evaluation-metrics sentiment-analysis

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updated: 2024-11-25 @ 05:12am, id: 178642919 / R_kgDOCqXf5w