/Senti-DD

Python implementation of Senti-DD

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Senti-DD

Python implementation of Senti-DD

  • Senti-DD
  • Direction-dependent words extracted from the entire DS50 dataset are listed on this page.
  • Evidence supporting the interpretable sentiment classification process for 2,259 headline sentences (FPB DS100 dataset) using the proposed Senti-DD lexicon is reported on this page.

Environments

pip install textblob afinn

Datasets

  • Financial Phrase Bank
    • Malo, Pekka, Ankur Sinha, Pekka Korhonen, Jyrki Wallenius, and Pyry Takala. "Good debt or bad debt: Detecting semantic orientations in economic texts." Journal of the Association for Information Science and Technology 65, no. 4 (2014): 782-796.
  • Subtask 2 of Task 5 in SemEval 2017
    • Cortis, Keith, André Freitas, Tobias Daudert, Manuela Huerlimann, Manel Zarrouk, Siegfried Handschuh, and Brian Davis. "Semeval-2017 task 5: Fine-grained sentiment analysis on financial microblogs and news." Association for Computational Linguistics (ACL), 2017.
  • Task 1 of the financial opinion mining and question answering (FiQA) challenge
    • Maia, Macedo, Siegfried Handschuh, André Freitas, Brian Davis, Ross McDermott, Manel Zarrouk, and Alexandra Balahur. "WWW’18 Open Challenge: Financial Opinion Mining and Question Answering." In Companion proceedings of the the web conference 2018, pp. 1941-1942. 2018.

Citation

In preparation