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esg-frontier

jupyter notebooks

  1. get_tweets/get_tweets.ipynb: uses twitter api v2 to retrieve tweets data and save them in get_tweets/ and get_tweets/tweets_data/ as .json files
    • requires twitter api keys
  2. get_tweets/merge_tweets.ipynb: cleans up and merge tweets data from relevant companies and save it to data/tweets_dow.csv
  3. train.ipynb: uses labeled data to train the nlp model via spacy, trained models are saved to output/
  4. tweets.ipynb: loads trained model to calculate climate-related score for each tweets, then aggregate into monthly scores for each stock

configuration files

  • conda-env.yml: create conda environment by conda env create -f conda-env.yml
  • config.cfg: for spacy training pipeline
  • keywords.txt: climate topic keywords, used to construct non-climate related labels
  • get_tweets/search_*.yaml: search queries for retrieving tweets in get_tweets.ipynb

csv files

  • data/tickers_dow.csv, data/tickers_sp_100.csv: stocks information
  • climate_score.csv: constructed monthly score for each stock

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