Professor of Information Qiaozhu Mei at the University of Michigan and colleagues developed a strategy to monitor the emotional health of workers and to predict work behaviors. The team tracked emoji use as a marker of emotions, and tracked how the use of emoji in work communications can predict remote worker dropouts.
The work is described in "Emojis Predict Dropouts of Remote Workers: An Empirical Study of Emoji Usage on GitHub," published in PLOS ONE.
The team used millions of GitHub posts as their source of remote-worker communications data, and employed machine learning to track the use of emoji in work-related online conversations. They trained their model to predict potential dropout of remote developers based on their emoji use.
They found that workers who regularly use emoji to express emotion — positive or negative — in their work may have better emotional health and are naturally less likely to drop off the platform one year later. The researchers also found that workers who don't use emoji are three times more likely to drop out of remote work.
From University of Michigan
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