Learn how Amenity Analytics’ NLP expertly handles the nuances and sophistication of human language. Amenity's unparalleled accuracy helps businesses make better decisions.
Thematic Sentiment (sometimes called "opinion mining") can be simply defined as the process of identifying and categorizing opinions found within text documents. In the broadest terms, thematic sentiment gauges the predominant opinion (whether positive, negative, or neutral) toward a subject of interest (commonly referred to as an “entity”) such as people, places, organizations, locations, and things.
This process often reveals valuable data that organizations can then use to guide their business strategies. For example, thematic sentiment analysis can be used to evaluate and analyze SEC filings, earnings call transcripts, corporate documents, and articles in the financial press.
Today's organizations have access to huge streams of text data: documents, discussions, reviews, blogs, news articles, and more.
While there are valuable nuggets of information waiting to be uncovered within these data streams, the process of sifting, sorting and analyzing all of this information is no small feat. It requires a significant outlay of time and money, not to mention the knowledge of a domain expert to interpret the data correctly.
So how do organizations surmount these obstacles? By using AI-driven solutions that can extract usable insights from any text data source at scale, while also displaying a sophisticated understanding human language.