CoVaxFrames: From Hesitancy Framings to Vaccine Hesitancy Profiles: A Journey of Stance, Ontological Commitments and Moral Foundations

This repository contains the annotations utilized in the following research paper:

From Hesitancy Framings to Vaccine Hesitancy Profiles: A Journey of Stance, Ontological Commitments and Moral Foundations

Please cite as the following:

@article{weinzierl2022hesitancy,
	title        = {From Hesitancy Framings to Vaccine Hesitancy Profiles: A Journey of Stance, Ontological Commitments and Moral Foundations},
	author       = {Weinzierl, Maxwell A. and Harabagiu, Sanda M.},
	year         = 2022,
	month        = {May},
	journal      = {Proceedings of the International AAAI Conference on Web and Social Media},
	volume       = 16,
	number       = 1,
	pages        = {1087--1097},
	url          = {https://ojs.aaai.org/index.php/ICWSM/article/view/19360}
}

CoVaxFrames

The CoVaxFrames collection is provided in the following file structure:

├── annotations                       # [tweet, framing] human judgements
│   ├── dev.jsonl                     # development split of {Accept, Reject, No Stance, Not Relevant} human judgements
│   ├── test.jsonl                    # testing split of {Accept, Reject, No Stance, Not Relevant} human judgements
│   └── train.jsonl                   # training split of {Accept, Reject, No Stance, Not Relevant} human judgements
└── taxonomy                          # Framing taxonomy judgements
   ├── frames.json                    # Framings with text as a json dictionary
   ├── frames.xlsx                    # Framings with framing taxonomy ids as an excel file
   ├── misinformation-concerns.xlsx   # Misinformation concerns
   ├── misinformation-themes.xlsx     # Misinformation themes
   ├── trust-building-concerns.xlsx   # Trust Building concerns
   ├── trust-building-themes.xlsx     # Trust Building themes
   ├── trust-eroding-concerns.xlsx    # Trust Eroding concerns
   ├── trust-eroding-themes.xlsx      # Trust Eroding themes
   └── questions.xlsx                 # Questions used to discover framings

You will need to use the Twitter API to download the text of the annotated tweets, as we cannot directly provide this info due to our IRB and Twitter's API policy.

Code

Code for the above research paper is provided in the following repository: Link