j0ma / cs140-sentiment-analysis-project

CS140 Sentiment Analysis Annotation Project

Instructions for annotators

Hello, dear annotator! ( ͡° ͜ʖ ͡°)

This repository contains our code and data for the CS140 group project on sentiment analysis.

In ./data/comments_for_annotators/<number> you will find 5 jsonl files, each corresponding to a 2020 presidential candidate.

Each file contains <number> comments, randomly sampled from the YouTube data set collected earlier in the semester. Note that potential values for <number> are 100, 200, and 500.

Your mission, should you choose to accept it, is as follows:

0. Fork this repository under your own name.
1. Set up a Python 3 development environment, e.g. using conda.
2. Install dependencies by running pip install -r requirements.txt
3. Go to ./Server/ and run python main.py
4. In your web browser of choice, navigate to https://localhost:5000
5. Click "Browse", navigate to ./data/comments_for_annotators/<number>, and choose the file <assigned_candidate>.<number>.jsonl. Afterwards, click "Upload".
6. Wait to be redirected and annotate.
   • If you need to revise an annotation, feel free to alter comment index in the URL to backward by your desired number of comments.
7. After annotating, your annotation file will be ./Server/annotations.jsonl
8. Rename your annotation file by running mv annotations.jsonl <candidate-last-name>-annotated-<your-name>.jsonl where <candidate-last-name> should be replaced with a lowercased version of the candidate's name, e.g. biden, and <your-name> should be lowercased and hyphenated, e.g. louis-brandeis.
9. Submit your annotations by committing to your own version of the repository, and submit a pull reqeuest to the original repository.

Good luck!! (•̀ᴗ•́)൬༉

Candidate-annotator assinments

Here is the schedule of candidate-annotator assignments:

Candidate	Annotator
Biden	Yonglin Wang
Buttigieg	Xiaoyu Lu
Sanders	Yonglin Wang
Warren	Zhuoran Huang
Yang	Xiaoyu Lu

Hint: you can double-check the random assignments by running

python scripts/assign_annotators.py

Links

• Sentiment Analysis @ NLP-progress