khanfarhan10/TextSentimentAnalysis
Text Sentiment Analysis in Python using Natural Language Processing (NLP) for Negative/Positive Content Detection. Deployed on the Cloud using Streamlit on the Heroku Platform.
This tool helps you quickly understand the overall mood or emotional tone of written content. You provide it with text, and it tells you whether the sentiment is generally positive or negative. It's ideal for anyone who needs to gauge public opinion, analyze customer feedback, or understand the emotional impact of written communication.
No commits in the last 6 months.
Use this if you need a straightforward way to determine the emotional tone (positive or negative) of text from sources like social media posts, reviews, or survey responses.
Not ideal if you require nuanced sentiment analysis, such as detecting specific emotions (e.g., joy, anger, surprise) or understanding sarcastic tones.
Stars
32
Forks
20
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 14, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/khanfarhan10/TextSentimentAnalysis"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
Davisy/Swahili-Tweet-Sentiment-Analysis-App
A simple app to analyze the sentiment of Swahili tweets.
BhaswatiRoy/Complete-Text-Analysis-Streamlit-Web-App
This is a Text Analysis App which can be used to find a detailed analysis of a particular text....
mathrailsAI/sentiment_insights
SentimentInsights is a Ruby gem for extracting actionable insights from qualitative survey...
netisheth/Churn-Prediction-and-Analysis
Extracted live tweets of customers by using Twitter APIs to create automatic rule-based churn...
harrychangjr/tiktok-analytics
Enhanced Tiktok dashboard using Streamlit and Plotly