Abstract
This paper introduces the augmented NTU sentiment dictionary, abbreviated as ANTUSD, which is constructed by collecting sentiment stats of words in several sentiment annotation work. A total of 26,021 words were collected in ANTUSD. For each word, the CopeOpi numerical sentiment score and the number of positive annotation, neutral annotation, negative annotation, non-opinionated annotation, and not-a-word annotation are provided. Words and their sentiment information in ANTUSD have been linked to the Chinese ontology E-HowNet to provide rich semantic information. We demonstrate the usage of ANTUSD in polarity classification of words, and the results show that a superior f-score 98.21 is achieved, which supports the usefulness of the ANTUSD. ANTUSD can be freely obtained through application from NLPSA lab, Academia Sinica: http://academiasinicanlplab.github.io/- Anthology ID:
- L16-1428
- Volume:
- Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
- Month:
- May
- Year:
- 2016
- Address:
- Portorož, Slovenia
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 2697–2702
- Language:
- URL:
- https://aclanthology.org/L16-1428
- DOI:
- Cite (ACL):
- Shih-Ming Wang and Lun-Wei Ku. 2016. ANTUSD: A Large Chinese Sentiment Dictionary. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2697–2702, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- ANTUSD: A Large Chinese Sentiment Dictionary (Wang & Ku, LREC 2016)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/L16-1428.pdf