Visionary companies like Amazon are leveraging sentiment analysis models to dig beyond surface-level understandings of what people are saying and examine the nuances of how it’s being said. However, sentiment in language is a difficult thing to parse. One person’s “negative” doesn’t always match their neighbor’s, and even short phrases can contain layers of nuance.
Those complications are only compounded when it comes to long-form writing like feature stories and product reviews. Ideally, the most sophisticated sentiment models could deliver broad-level, composite scores for long-form content, while simultaneously sifting through individual paragraphs, sentences, and words to extract granular-level insights.
When Amazon wanted to turn that ideal into a reality, they partnered with DefinedCrowd.