@inproceedings{L16-1428,
 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/
},
 address = {Portorož, Slovenia},
 author = {Shih-Ming Wang and Lun-Wei Ku},
 booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
 month = {May},
 pages = {2697--2702},
 publisher = {European Language Resources Association (ELRA)},
 title = {ANTUSD: A Large Chinese Sentiment Dictionary},
 url = {https://www.aclweb.org/anthology/L16-1428},
 year = {2016}
}