SannketNikam / Emotion-Detection-in-Text

This project employs emotion detection in textual data, specifically trained on Twitter data comprising tweets labeled with corresponding emotions. It seamlessly takes text inputs and provides the most fitting emotion assigned to it.

Date Created 2023-04-02 (about a year ago)

Commits 22 (last one 4 months ago)

Stargazers 40 (0 this week)

Watchers 1 (0 this week)

Forks 15

License unknown

Ranking

RepositoryStats indexes 622,269 repositories, of these SannketNikam/Emotion-Detection-in-Text is ranked #544,927 (12th percentile) for total stargazers, and #560,891 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #15,274/18,620.

SannketNikam/Emotion-Detection-in-Text is also tagged with popular topics, for these it's ranked: machine-learning (#7,596/8312), nlp (#2,264/2496), data-science (#2,037/2201), streamlit (#333/430), sentiment-analysis (#223/257)

Other Information

SannketNikam/Emotion-Detection-in-Text has Github issues enabled, there are 2 open issues and 1 closed issue.

All Topics

nlp nltk tf-idf stemming word2vec stopwords streamlit wordcloud data-science lemmatization multinomialnb streamlit-cloud count-vectorizer machine-learning model-deployment streamlit-webapp emotion-detection sentiment-analysis logistic-regression

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Recent Commit History

22 commits on the default branch (main) since jan '22

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Languages

The primary language is Jupyter Notebook but there's also others...

updated: 2025-03-04 @ 10:01am, id: 622573448 / R_kgDOJRu3iA