What is Sentiment Analysis?

Sentiment analysis refers to the process of analyzing and interpreting the emotions, attitudes, and opinions expressed in textual data such as social media posts, customer reviews, or survey responses. Actian’s sentiment analysis solutions aim to uncover the underlying sentiment or tone behind these pieces of text, helping businesses gain insights into customer feedback, market trends, and public perception.

Actian’s sentiment analysis algorithms utilize natural language processing (NLP) techniques to assess the sentiment of the text as either positive, negative, or neutral. These algorithms take into account various linguistic and contextual factors, including word choice, sentence structure, and sentiment-bearing phrases, to determine the overall sentiment of the text.

Confidence messaging is an important aspect of Actian’s sentiment analysis offering. It represents a measure of the algorithm’s certainty or confidence in the assigned sentiment label. Actian’s solutions typically provide a confidence score or rating along with the sentiment classification, indicating the level of reliability or certainty associated with the result.

The confidence messaging can help businesses understand the level of trust they can place in the analysis results. Higher confidence scores indicate a greater degree of certainty in the sentiment classification, while lower scores suggest a higher likelihood of potential errors or ambiguity. By considering the confidence messaging, Actian’s clients can make informed decisions based on the sentiment analysis outputs, understanding the level of reliability and potential risks associated with the results.