Num-Symbolic Homophonic Social Net-Words

Yi Liang Chung, Ping Yu Hsu, Shih Hsiang Huang

Research output: Contribution to journalArticlepeer-review

Abstract

Many excellent studies about social networks and text analyses can be found in the literature, facilitating the rapid development of automated text analysis technology. Due to the lack of natural separators in Chinese, the text numbers and symbols also have their original literal meaning. Thus, combining Chinese characters with numbers and symbols in user-generated content is a challenge for the current analytic approaches and procedures. Therefore, we propose a new hybrid method for detecting blended numeric and symbolic homophony Chinese neologisms (BNShCNs). Interpretation of the words’ actual semantics was performed according to their independence and relative position in context. This study obtained a shortlist using a probability approach from internet-collected user-generated content; subsequently, we evaluated the shortlist by contextualizing word-embedded vectors for BNShCN detection. The experiments show that the proposed method efficiently extracted BNShCNs from user-generated content.

Original languageEnglish
Article number174
JournalInformation (Switzerland)
Volume13
Issue number4
DOIs
StatePublished - Apr 2022

Keywords

  • homophonic
  • net-word
  • text analysis
  • user-generated content

Fingerprint

Dive into the research topics of 'Num-Symbolic Homophonic Social Net-Words'. Together they form a unique fingerprint.

Cite this