Science Score: 41.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (13.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: hiralbhanu
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 1.24 MB
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  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Created over 4 years ago · Last pushed over 4 years ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

SE-Project-Group-38

Sentiment Analyser

A software that predicts the sentiment of the sentences a person enters.

Licence DOI codecov

Video of the Software

https://user-images.githubusercontent.com/43321682/135562787-845cd363-cb9d-4f54-b117-d97d24ba73f3.mp4

Use Cases

  • E-Commerce websites and companies can easily find the sentiments of its users by analysing their reviews.

Installation

  • Clone the repository using git clone https://github.com/hiralbhanu/Sentiment_Analyser.git
  • Create a python virtual environment with the following command : python3 -m venv
  • Activate the virtual environment with the following command : source /bin/activate
  • Run the following command to install all the necessary modules for the project to work : pip install -r requirements.txt
  • (Only for M1 MacBook Air/Pro users) : If either scipy/lime is not installing, run the shell script “scriptmacos.sh” by typing “./scriptmacos.sh” on the terminal. Repeat step 4 and the packages should install without any issues.

Running Application

  • Type “python3 app.py” in the virtual environment on the terminal in order to run the flask web application. Open the URL on a web browser.
  • Enter the sentence to be tested, select the number of samples to be generated by the lime explainer on the next line
  • Select the model and press “Go”

Languages

  • Python
  • HTML
  • CSS

Software Requirements

  • Python
  • Flask

"Why" and "Why not" Sentiment Analyser

  • Sites like Amazon cannot read each and every review of its users. Instead they can use this software to find the overall sentiment of the reviews of the customers of a particular product.

Team Members

  • Hiral Bhanushali
  • Hrushabh Chouhan
  • Apoorva Chauhan
  • Angela Ho

Owner

  • Name: Hiral Bhanushali
  • Login: hiralbhanu
  • Kind: user

Citation (CITATION.md)

Cite as ...
Group 38, Sentiment Analyser, September 2021

citation-version: 1.0.0 message: "Following is the format if you want to cite the software or system" authors:

family-name: "Chauhan" given-name: "Apoorva"

family-name: "Chouhan" given-name: "Hrushabhsingh"

family-name: "Bhanushali" given-name: "Hiral"

family-name: "Ho" given-name: "Angela"


title: "Software Engineering(CSC510): Project-Group-38" version: v1.0.0 doi: 10.5281/zenodo.5533076 date-released: 09/27/2021 url: "https://doi.org/10.5281/zenodo.5542211"

@article{g15:Project 1,
	title 	  = {Sentiment Analysis},
	DOI 	  = {10.5281/zenodo.5542211},
	author    = {Group 38},
	publisher = {Zenodo},
	year      = {2021},
	month     = {September}
}

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Dependencies

requirements.txt pypi
  • argparse *
  • cython *
  • flask *
  • lime *
  • numpy *
  • pandas *
  • pathlib *
  • scipy *
  • sklearn *
  • spacy *
  • textblob *
  • tqdm *
  • typing *
setup.py pypi
  • argparse *
  • cython *
  • flask *
  • lime *
  • numpy *
  • pandas *
  • pathlib *
  • scipy *
  • sklearn *
  • spacy *
  • textblob *
  • tqdm *
  • typing *