An empirical analysis of emoji usage on Twitter

Mengdi Li, Eugene Chng, Alain Yee Loong Chong, Simon See

Research output: Journal PublicationArticlepeer-review

13 Citations (Scopus)

Abstract

Purpose: Emoji has become an essential component of any digital communication and its importance can be attested to by its sustained popularity and widespread use. However, research in Emojis is rarely to be seen due to the lack of data at a greater scale. The purpose of this paper is to systematically analyse and compare the usage of Emojis in a cross-cultural manner. Design/methodology/approach: This research conducted an empirical analysis using a large-scale, cross-regional emoji usage data set from Twitter, a platform where the limited 140 characters allowance has made it essential for the inclusion of emojis within tweets. The extremely large textual data set covers a period of only two months, but the 673m tweets authored by more than 2,081,542 unique users is a sufficiently large sample for the authors to yield significant results. Findings: This research discovered that the categories and frequencies of Emojis communicated by users can provide a rich source of data to understand cultural differences between Twitter users from a large range of demographics. This research subsequently demonstrated the preferential use of Emojis complies with Hofstede’s Cultural Dimensions Model, in which different representations of demographics and culture within countries present significantly different use of Emojis to communicate emotions. Originality/value: This study provides a robust example of how to strategically conduct research using large-scale emoji data to pursue research questions previously difficult. To the best of authors’ knowledge, the present study pioneers the first systematic analysis and comparison of the usage of emojis on Twitter across different cultures; it is the largest, in terms of the scale study of emoji usage to-date.

Original languageEnglish
Pages (from-to)1748-1763
Number of pages16
JournalIndustrial Management and Data Systems
Volume119
Issue number8
DOIs
Publication statusPublished - 19 Sep 2019

Keywords

  • Data mining
  • Emoji
  • Empirical analysis
  • Social media
  • Twitter

ASJC Scopus subject areas

  • Management Information Systems
  • Industrial relations
  • Computer Science Applications
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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