thunlp/NSC
Neural Sentiment Classification
This project helps you understand the overall sentiment expressed in documents like customer reviews, movie reviews, or social media posts. You provide raw text data, potentially alongside user and product identifiers, and it classifies the sentiment (e.g., positive, negative) to give you an overview of public opinion. This is for market researchers, product managers, or anyone needing to quickly gauge audience feelings from large text collections.
287 stars. No commits in the last 6 months.
Use this if you need to automatically categorize the sentiment of text data, such as product reviews or movie feedback, with high accuracy by considering user and product context.
Not ideal if you need to understand sentiment at a granular phrase level within a document, or if you require real-time sentiment analysis on streaming data.
Stars
287
Forks
93
Language
Python
License
MIT
Category
Last pushed
Apr 13, 2018
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/thunlp/NSC"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
laugustyniak/awesome-sentiment-analysis
Repository with all what is necessary for sentiment analysis and related areas
binodmx/helasentilex
Python API for Sinhala Sentiment Lexicon
GoogleCloudPlatform/dataflow-opinion-analysis
Opinion Analysis of News, Threaded Conversations, and User Generated Content
Ruthwik/Sentiment-Analysis
Sentiment Analysis using Stanford CoreNLP.
bhadreshpsavani/ExploringSentimentalAnalysis
This Repository Contains Different ways to do sentimental Analysis