"Stress @ Work" reads incoming Facebook, Twitter and text messages for tone and color-codes so users know if the message is nice, neutral or negative. The app is meant to warn users of texts containing hostile words so they can prepare themselves before reading and better manage their stress.
Under an approach called sentiment analysis, the app uses a pre-trained algorithm that determines whether text and email communications will make users happy. Nice messages receive the green stamp of approval, neutral messages are designated as blue and negative messages are color-coded red.
By anticipating the type of message they are about to read, texters can "manage their stress in the best possible way," senior lecturer Mohamed Medhat Gaber, who helped develop the app, told BBC.
"Whether we are reading a worrying social media news story or a warning email from our manager, messages can upset mood and increase stress level, just as good news and encouraging emails can cheer you up," Gaber said in a prepared statement.
Like smartphones that develop a working knowledge of anticipated words in a text conversation, "Stress @ Work" enables users to manually designate individual messages as positive or negative in order for it to better predict the user's perception of good and bad.
"The application works by learning from past messages how the user perceives the content as being positive, negative or objective," Gaber told BBC.
However, once an Android user reviews the color of a text, deciding whether to read it and how to manage their stress is up to them. "Stress @ Work" merely acts a warning tool, preparing users for bad news.
Chambers and Gaber will present the app at the 16th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems in Spain in September and hope to debut the app for free on Google Play shortly thereafter. Though "Stress @ Work" has only been tested on Android OS, an iOS version may be in the works.
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