Innovation in Language Learning

Edition 16

Accepted Abstracts

A Corpus-Based Study on Web-Based Chinese Lettered Words

Jing Wu, University of Hawaiʻi at Mānoa (United States)


The worldwide pandemic has accelerated the transition to a digital world. As a result of rapid globalization and English as an international lingua franca in the digital era, a boost of lettered word utilization has been witnessed in contemporary Chinese internet language. Insomuch that a series of questions have arisen—(a) In which domains of life are the lettered words more commonly used in recent times? (b) What are their salient typological and grammatical features? (c) What are the prevailing attitudes and stipulations concerning the usage of the lettered words in China? (d) What are the rationalities and inevitabilities of the existence of the lettered words? Thereby, this preliminary study, through scrutinizing an extensive collection of Mandarin Alphabetic Words from Sina Weibo (hereinafter SMAW) dataset constructed by Xiang et al. (2020), is intended to fill a lacuna in existing research and provide an exploration of the lettered words in Web-based language. It attempts to dissect the SMAW corpus data by profiling semantic domains, typological features, and grammatical forms of a group of most commonly used lettered words; then, compare several previous pertinent studies and examine whether findings are consistent with the previous results. Moreover, disputations and provisions pertaining to the lettered word utilization are discussed. In conclusion, this study probes the presence of such language mixing phenomena in linguistic and sociolinguistic dimensions and then endeavors to ascertain future prospects of the Chinese lettered words from an ecolinguistic perspective.

Keywords: Chinese lettered words, Weibo-based, typological, semantic, ecolinguistic.


  • Xiang, R., Wan, M. Y., Su, Q., Huang, C. R., & Lu, Q. (2020). Sina Mandarin alphabetical words: A Web-driven code-mixing lexical resource. Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing. 833–842.

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