Git Product home page Git Product logo

sentiment_analysis's Introduction

Sentiment Analysis

  1. Project Overview
  2. Installation
  3. Data
  4. Implementation
  5. Results

1. Project Overview

This project to build a sentiment analysis for English Movies dataset and Arabic Posts.

2. Installation

  • Python versions 3.*.
  • Python Libraries:
    • sklearn.
    • Pandas.
    • string.
    • nltk
    • re.

3. Data

English

IMDB dataset having 50K movie reviews. This is a dataset for binary sentiment classification.

Arabic

BBN Blog Posts Sentiment Corpus contains A random subset of 1200 sentences chosen from the BBN Arabic-Dialect–English Parallel Text.

4. Implementation

In this project, we used Gaussian Naive Bayes from scikit-learn. The data have been split into training and testing with a ratio of 80:20.

English

Arabic

5. Result

Here some prediction to model.

English

Arabic

sentiment_analysis's People

Contributors

zarahshibli avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.