Are you interested in tools to track how customers feel about something? Or tools to gauge how they feel about a recently launched product in their posts in social media sites? Or tools to analyze what callers say in their interactions with some agent? The solution to your quest is in sentiment analysis, with the aid of AI models.
What is Sentiment Analysis?
NLP (Natural Language Processing), AI (Artificial Intelligence) and ML (Machine Learning) generate algorithms that automatically spot and identify sentiments in text data, for classification and analysis. Sentiment Analysis or Sentiment Mining determines individual judgement toward a product or an idea.
Product teams device tools that use Sentiment Analysis or Sentiment Mining to skim comments on a news article, or reviews about a brand, a company, a product, a service, etc., in social media posts, interviews, phone calls and the like. The gathered information will be the basis for a market research to inform organizations so as to decide upon improvements, resources, and other useful decisions.
Likewise, Intention Analysis and Emotion Detection round up the information collected and classified by means of NLP. Intention Analysis detects opinion, feedback, complaint, etc. Emotion Detection detects happiness, anger, satisfaction and other feelings. These tools work together to find out and classify sentiments in strings of static text or audios. Thus models work out a report within a range between -1 and 1, i.e. sentiment polarity.
Best API for Sentiment Analysis
If you are looking to perform Sentiment Analysis on data text, audio or video, Zyla Labs Sentiment Analysis API is an outstanding option. It offers accurate reports for product teams and developers, with the advantage of competitive pricing in the market today. Its model assesses sentiment polarity so as to define the probability that the segments analysed are positive, negative or neutral.
The application of scores and ratios will result in accurate information for the organization. The thorough evaluation in entities or keywords helps organizations and developers to better comprehend the public sentiment about a given product, brand or service.
This API is an essential tool for telephony companies, for example, to extract customer feelings and feedback and to analyse agent behaviour as well. Product teams use Sentiment Analysis at virtual meeting platforms to track sentiments in participants by means of portion meeting, meeting topic, meeting time, etc. This is a powerful analytic instrument to make better decisions so as to make improvements and adjustments.
Sentiment Analysis has lately gained worldwide reputation as one of the text analytics applications. Companies that have not implemented this yet must recourse on this tool for benefiting from this technology. The above described solution renders coding packages and no-code tools for organizations to be able to run pilots of Sentiment Analysis so as to determine the business value that Zyla Labs Sentiment Analysis API can bring to them.
Get this API to find accurate, granular insights from multiple sources, in real time. Do not miss judgement in translation, as it provides native language analysis for several languages. It offers machine learning to monitor changes in local language, and even in slang and specific jargon to guarantee that your data is always updated. There is easy integration with the tech stack you already use. The sooner you try, the prompter your results will be!