  Emotions at work have long been identified as critical signals of work
motivations, status, and attitudes, and as predictors of various work-related
outcomes. For example, harmonious passion increases commitment at work but
stress reduces sustainability and leads to burnouts. When more and more
employees work remotely, these emotional and mental health signals of workers
become harder to observe through daily, face-to-face communications.
  The use of online platforms to communicate and collaborate at work provides
an alternative channel to monitor the emotions of workers. This paper studies
how emojis, as non-verbal cues in online communications, can be used for such
purposes. In particular, we study how the developers on GitHub use emojis in
their work-related activities. We show that developers have diverse patterns of
emoji usage, which highly correlate to their working status including activity
levels, types of work, types of communications, time management, and other
behavioral patterns. Developers who use emojis in their posts are significantly
less likely to dropout from the online work platform. Surprisingly, solely
using emoji usage as features, standard machine learning models can predict
future dropouts of developers at a satisfactory accuracy.
