Table of Contents
A mobile app that determines the sentiment (positive, negative, neutral) of a topic based on conversations happening on Twitter by leveraging natural language processing and machine learning.
To get a local copy up and running follow these simple example steps.
- Twitter Developers Account
- Twitter Account
-
Download or clone this repo
$ git clone [email protected]:ellojess/Twitter-Sentiment-iOS.git
-
Get your free credentials from Twitter at https://developer.twitter.com/en/dashboard
Use the credentials from the Developers Account to get the following values.
Add them in the
Constants.swift
file by replacing VALUE with your personal credentialslet apiKey="VALUE" let apiSecretKey="VALUE" let bearerToken="VALUE"
-
cd
into the project folder and open it in Xcode (or usexed .
to open it from terminal)$ cd Twitter-Sentiment $ xed .
-
If your local project has an error with
Swifter
you can deleteSwifteriOS
from the file hierarchyThen download and embed
SwifteriOS
from here
See the open issues for a list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request using this template
- Add a new feature (accessibilities, etc.)
- New UI elements (animations, dark-mode, etc)
- Increase accuracy of model (handle sarcasm & emojis)
Distributed under the MIT License. See LICENSE
for more information.
Jessica Trinh - @ellojesss - [email protected]
Project Link: https://github.com/ellojess/Twitter-Sentiment-iOS
- Swift
- SwiftUI
- CoreML
- SwifteriOS
- SwiftyJSON
- Twitter Sanders Apple3 dataset