ANTUSD: A Large Chinese Sentiment Dictionary

Shih-Ming Wang, Lun-Wei Ku


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:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/L16-1428.pdf