Sentiment analysis, stemming and lemmatization, part-of-speech tagging and chunking, phrase extraction and named entity recognition.
One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences.
Multilingual sentiment analysis of texts from different sources (blogs, social networks,...). Besides polarity at sentence and global level, Sentiment Analysis uses advanced natural language processing techniques to also detect the polarity associated to both entities and concepts in the text. Sentiment Analysis also gives the user the possibility of detecting the polarity of user-defined entities and concepts, making the service a flexible tool applicable to any kind of scenario. Additionally, Sentiment Analysis detects if the text processed is subjective or objective and if it contains irony marks [beta], both at global and sentence level, giving the user additional information about the reliability of the polarity obtained from the sentiment analysis.
Discover the sentiment behind the inputted text with the best sentiment analysis APIs.
A sentiment analysis application programming interface (API) is a service that enables developers to add sentiment extraction functionality into their applications or websites. Sentiment analysis is also referred to as “contextual mining” or “opinion mining.” The API determines if the sentiment (the attitude or emotion behind what was written) has a positive, negative, or neutral tone.
The API for sentiment analysis uses POST and GET requests to communicate with the service. JSON-formatted responses are returned in the request body. Sentiment analysis uses artificial intelligence (AI) technology, specifically, natural language processing (NLP) to analyze text. In addition, text analysis techniques and linguistics help determine the sentiment of the text.
Developers that want to save time coding the sentiment function into their applications will benefit from using sentiment analysis APIs.
Businesses that want to understand how consumers receive their brand will find sentiment APIs insightful tools.
The best sentiment analysis APIs are advantageous to developers because they only require a few lines of code to implement. To connect to the service, developers use endpoints provided by the API. By doing so, they can avoid taking a great deal of time to learn NLP code and concepts.
Businesses that measure sentiment analysis may have a competitive edge. When brands learn how consumers truly feel about their products and services, it helps them assess their marketing campaigns.
Developers can expect to build applications with reliable connections to data resources that measure emotional intent. And they can do this without writing or debugging code for that function.
Businesses can expect to gain deeper insights into the value that their products and service offerings bring to their customers. They can then take that information to improve their products, encourage brand loyalty, and solidify their brand’s presence in their industry.
There are several free and freemium APIs for sentiment analysis listed on RapidAPI’s Marketplace. Sentiment Analysis by Twinword analyzes the tone of the inputted text. Its Basic freemium plan is free and includes a 500-request quota per month. The cost of overages is small.
Another API on the Marketplace is Text Sentiment Analysis Method by Fyhao. The API offers one option: free.
Just select your preference from any API endpoints page.
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