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Whether users perceive an app as bold, quirky, professional, or cute depends primarily on the copy.
Different cultures and individuals can have different reactions to similar content posted online, so brands need to make sure that their message is being received as intended.
Now, a company aims to manage all the words in the online user experience.
San Francisco-based Qordoba has released a product that gives users relevant online content to resonate with users. Its Strings Intelligence Platform enables product teams to manage all words across their products.
Its machine learning-based solution extracts text from strings in source code to make words accessible and measurable across platforms.
It integrates unsupervised machine learning-based affect detection between online video and text, and it allows users to measure the emotional content of online copy across 21 languages.
It has capability to score emotional tone in online content and measures the emotional content of copy to improve the user's online experience. It analyses and measures copy for brand consistency, emotional tone, style, vocabulary, and grammar.
The content scoring mechanism is based on Affect Detection. This is a computer science discipline that applies artificial intelligence and machine learning to understand the primary emotion conveyed by written text.