Search Results for author:
Found 8 papers, 3 papers with code
From Adoption to Adaption: Tracing the Diffusion of New Emojis on Twitter
In the rapidly evolving landscape of social media, the introduction of new emojis in Unicode release versions presents a structured opportunity to explore digital language evolution.
Emojis Decoded: Leveraging ChatGPT for Enhanced Understanding in Social Media Communications
Our objective is to validate the hypothesis that ChatGPT can serve as a viable alternative to human annotators in emoji research and that its ability to explain emoji meanings can enhance clarity and transparency in online communications.
Emoji Promotes Developer Participation and Issue Resolution on GitHub
In this paper, we study how emoji usage influences developer participation and issue resolution in virtual workspaces.
Team Resilience under Shock: An Empirical Analysis of GitHub Repositories during Early COVID-19 Pandemic
While many organizations have shifted to working remotely during the COVID-19 pandemic, how the remote workforce and the remote teams are influenced by and would respond to this and future shocks remain largely unknown.
Emojis predict dropouts of remote workers: An empirical study of emoji usage on GitHub
This paper studies how emojis, as non-verbal cues in online communications, can be used for such purposes and how the emotional signals in emoji usage can be used to predict future behavior of workers.
SEntiMoji: An Emoji-Powered Learning Approach for Sentiment Analysis in Software Engineering
However, commonly used out-of-the-box sentiment analysis tools cannot obtain reliable results on SE tasks and the misunderstanding of technical jargon is demonstrated to be the main reason.
A First Look at Emoji Usage on GitHub: An Empirical Study
We find that emojis are used by a considerable proportion of GitHub users.
Computers and Society Software Engineering
Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification
To tackle this problem, cross-lingual sentiment classification approaches aim to transfer knowledge learned from one language that has abundant labeled examples (i. e., the source language, usually English) to another language with fewer labels (i. e., the target language).
