Skip to content

Latest commit

 

History

History
33 lines (25 loc) · 2.09 KB

README.md

File metadata and controls

33 lines (25 loc) · 2.09 KB
Raw

Sentiment Analyzer

Analyze the sentiment of a text stored in a string or text file and understand the reason why your blogs and posts are not ranking up. This Model is developed using Python3 programming language without using nltk package.

How to use it ?

  • If you want to use it from online api, then visit "https://sentimentanalyzer.vercel.app/analyze?text=your+text+here" and it will return you a json object which contains output.
  • or you can download the source code of this model on your system and use it as you want.
  • Install Python3 on your system from here.
  • Download this repository from here.
  • After downloading, extract the zip file and open the extracted folder.

Files & Folders:

  1. "app.py": It is a python file which is used to handle request on backend.
  2. "Model" : This folder contains the main API. It contains files like :

    • "support_files": this folder is used by "Corrector_generator.ipynb" to generate "Corrector.json".

    • "Corrector.json": this file contains all the words required to clean your given text which eventually increases accuracy and quality of output.

    • "Corrector_generator.ipynb": this is a jupyter notebook file of a python script which helps you to generate and update "Corrector.json".

    • "AnalystUtility.py": this file contains the implementation of neccesary formula required to create outputs.

    • "Analyzer.py": this is the main file which contains the implementation and logic of this Analyzer. It contains two functions :

      1. Analyze_String(val : str) : this function takes string as input as returns a dictionary as output.

      2. Analyze_File(file_name : str) : this function takes file address as a input and returns a dictionary as output.

Developer Info: