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Chinese Irony Corpus Construction and Ironic Structure Analysis

Summary

Irony flips a statement's literal meaning, which misleads opinion mining and sentiment analysis. Chinese had no irony corpus, and hashtag collection works poorly for it: Weibo held only 113 posts tagged #反諷. Tang and Chen built a corpus from Traditional Chinese posts on the Plurk microblog. They treated negative emoticons as the poster's real feeling and positive words from NTUSD as the surface sentiment, so a mismatch marked a candidate. They dropped posts where a positive word comes before a contrastive connective like "but", since that polarity shift is literal. Bootstrapping began with a degree adverb plus positive adjective template and used the CKIP parser for POS tags. Each round, an annotator checked retrieved posts and added newly spotted patterns. The process yielded five pattern types and the NTU Irony Corpus. The authors also describe irony as having two required parts, an ironic word or phrase and context, plus optional rhetorical intensifiers. Context may stay implicit unless it is linguistic. Every message is tagged with these elements. The paper presents this as the first Chinese irony corpus.

Key points

  • Source data: Plurk posts from June 2008 to November 2009. Of 35 emoticons, 23 count as positive and 12 as negative. NTUSD supplies 21,056 positive and 22,751 negative words.
  • Filtering funnel:
    • 3,178,372 posts with a negative emoticon;
    • 304,754 of those also contain a positive word;
    • 254,836 remain after connective filtering;
    • 2,825 match a pattern after four bootstrapping rounds;
    • 1,005 are confirmed ironic and form the publicly released NTU Irony Corpus.
  • Pattern frequencies: degree adverb + positive adjective appears in 13.03% of corpus messages. High-intensity positive adjectives (e.g., 偉大, 了不起, 天才) appear in 2.09%. High-intensity positive nouns (e.g., 巨星, 大禮) form another of the five groups.
  • Annotation scheme: each message carries <ironic>, <context> and <rhetoric> tags, with sentiment polarity attributes on the ironic and context elements.
  • Platform and genre findings: 83.19% of Weibo #反諷 posts show no hyperbole or intensifiers, which makes hashtags weak for pattern mining. A comparison with Yahoo texts suggests customary patterns dominate informal, conversational writing, while non-customary forms appear more in formal articles.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Cited by

8 papers of our library cite it (of the 140673 whose bibliographies we read); 3 of them have a page here, 5 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work.

@inproceedings{tang2014chinese,
  title = {{Chinese Irony Corpus Construction and Ironic Structure Analysis}},
  author = {Tang, Yi-jie and Chen, Hsin-Hsi},
  booktitle = {Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers},
  year = {2014},
  url = {https://aclanthology.org/C14-1120/}
}

References

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