OpenFraming

Introduction

We have introduced OpenFraming, a Web-based system for analyzing and classifying frames in the text documents. OpenFraming is designed to lower the barriers to applying machine learning for frame analysis, including giving researchers the capability to build models using their own labeled data. Its architecture is designed to be user-friendly and easily navigable, empowering researchers to com- fortably make sense of their text corpora without specific machine learning knowledge.

You can find the preprint of our work here

Requirements

Docker

You need Docker. Feel free to read up on Docker if you wish. Our best short explanation for Docker is that, Docker is for deploying applications with complicated dependencies, what the printing press was to publishing books (it allows you to do it in a much quicker, and much more reproducible way).

The link above has guides on how to install Docker on the most popular platforms.

How to install

git clone https://github.com/davidatbu/openFraming.git
cd openFraming
docker-compose build
docker-compose up

You might have to add sudo at the beginning of commands at step 3 and 4.

E-mails

If you want to send actual e-mails through Sendgrid with this system (as opposed to just printing the e-mails that would be sent to the console), please set the environment variables:

export SENDGRID_API_KEY=     # An API key from Sendgrid
export SENGRID_FROM_EMAIL=   # An email address to put in the "from" field. Note that
                 # you'll have to verify this email in Sendgrid as a 
                 # "Sender".

If you happen to need sudo in the section above, please pass the -E flag to make sure these environment variables are picked up. i.e.,

sudo -E docker-compose up

Video demonstration

You can check the following YouTube video for a quick demonstration of our Website's features.

Getting help

If you have any question, concern, or bug report, please file an issue in this repository's Issue Tracker and we will respond accordingly.

Citation

@article{smith2020openframing,
  title={OpenFraming: We brought the ML; you bring the data. Interact with your data and discover its frames},
  author={Smith, Alyssa and Tofu, David Assefa and Jalal, Mona and Halim, Edward Edberg and Sun, Yimeng and Akavoor, Vidya and Betke, Margrit and Ishwar, Prakash and Guo, Lei and Wijaya, Derry},
  journal={arXiv preprint arXiv:2008.06974},
  year={2020}
}

Funding

This research is funded by the following NSF Award:

NSF Award #1838193 BIGDATA: IA: Multiplatform, Multilingual, and Multimodal Tools for Analyzing Public Communication in over 100 Languages

Acknowledgement

We are truly grateful to Gerard Shockley, Boston University Cloud Broker, for helping us seamlessly host our Website and run in an Amazon Web Services EC2 instance.

Credits

Alyssa Smith^*, David Assefa Tofu^*, Mona Jalal^*, Edward Edberg Halim, Yimeng Sun, Vidya Prasad Akavoor, Margrit Betke, Prakash Ishwar, Lei Guo, Derry Wijaya

dnaaun / openFraming

readme