Sentiment Analysis is the systematic identification, extraction, quantification and analysis of emotional states and personal judgement by means of NLP (Natural Language Processing), text analysis, computational linguistics and biometrics. This is an important tool to define if the author´s sentiment towards an organization, a product, a service is positive, negative or neutral.
It is essential for developers to make use of an API to analyze sentiment so as to be able to understand the users` attitude. With this information, developers can build tools for gauging and reporting to draw more accurate insights and make better decisions. Basically, thanks to Sentiment Analysis APIs developers pulse the users` sentiment and prevent their telling others about bad experiences in posts on social media sites. But this is only one of the several reasons why these APIs are important to developers.
Zyla Labs Sentiment Analysis API renders multilingual identification of polarity in any text. This will allow developers to gather a precise sentiment from customers so as to decide on and suggest improvements on the basis of such data. The API can identify facts from opinions, and will also detect irony and disagreement. It makes dictionaries available so as to adapt analysis to the developer`s requirements and needs.
The versatility of this API allows users who have loads of responses or reviews to analyze, to spot the negative comments at once. The resulting score will show how positive, negative or neutral the total amount of text analyzed is, rating within a -0.05 and 0.05 range. Texts can be interpreted according to the developers´ intention, with the aim of creating their own negative and positive minimum scores.
The API extrapolates sentiment in a selected string of text. By means of NLP and other relevant tools it identifies and detects subjective information from a given text. The algorithm selects and classifies every sentence in the input. It also detects variants of the resulting judgements as very negative and very positive.
Zyla Labs Sentiment Analysis API also grants text classification, emotion analysis, topic tagging, text similarity, word associations, entity analysis, content classification, as well as many other functions, which will result in more accurate and useful applications. This API can detect what lies beneath the text, the meta-data to make sentiment detection more precise. All this information will allow developers to generate more AI applications to better understand human expression. It guarantees the use of a wide range of machine learning tools and services.
Developers are able to identify key phrases and examine positive or negative sentiments about specific topics. No matter whether the text is structured or not, the API will decode text data with hardly any machine learning experience. All these features grant the ability to a fast assessment and identification of the relevant points in any text.
How to get started
Once the developer signs up, he is assigned a personal API access key, which is an exclusive combination of symbols for access to Zyla Labs Sentiment Analysis API. You will be requested to validate the account by means of Emotion Detection API REST API, for which you just include your token in the Authorization Header.
If your purpose is to augment functionality to your web or mobile app, be sure to check out this API, as you can be certain of getting accuracy in the collected data and metadata.