Text Analysis APIs

Text Analysis APIs leverage AI and NLP to dissect large bodies of text, offering functionalities such as translation, fact extraction, sentiment analysis, and keyword research.Businesses and consumers can benefit from these APIs for tasks like data mining, article spinning, and sentiment analysis, enhancing various processes and decision-making capabilities.

Text Analysis APIs

About Text Analysis

Machine-based text analysis allows users to parse large bodies of texts and extract meaningful data. APIs offer access to third-party solutions that can translate, extract facts, semantics, keywords or even spin the content into unique versions.

What is a Text Analysis API?

A text analysis API is pre-trained and utilizes artificial intelligence and neuro-linguistic programming to dissect large bodies of words. Businesses and consumers alike can use them for data mining, sentiment analysis, keyword research, article scraping or spinning, and much more.

How does a Text Analysis API work?

Text analysis APIs are usually built on REST protocols. Commands are sent from the application through the API that tells it what type of operation is required. The API then follows the path to the server, extracts the requested information, and returns the data to the end-user with any needed adjustments (like translations).

Who can benefit from Text Analysis APIs?

There are many use cases for APIs that analyze text. Just a few ways that different entities can benefit are:

  • Researchers can extract facts and figures from large amounts of data.
  • Companies can better understand customer sentiment and intent by using machines to analyze comments and reviews.
  • Developers can build translation services into their applications, which effectively broadens their audience and user base.
  • Website owners can make their content search engine optimization (SEO) friendly by performing keyword research on the competition and modeling their own content to the highest performing sites in their niche.

Why are Text Analysis APIs necessary?

An excellent example of the importance of text analysis is Project Gutenberg. The project’s initial goal, which began in 1971, was to digitize the top 10 thousand most publicly consulted works, starting with the Declaration of Independence. Up until 1989, human volunteers manually entered all texts. However, once optical character recognition software and image scanners improved, the labor was turned over to machines, making the process infinitely quicker as a result.

Today, text analysis has expanded into being an integral part of our everyday lives. We as a society benefit in many ways, such as reading ancient texts translated into our native languages, companies understanding our needs better by analyzing our reactions to their products, and much more.

What can you expect from a Text Analysis API?

Developers should look for clean code that offers both security and flexibility. As these types of APIs often make a large number of call requests, taking the pricing structure into account for your application is vital, as your end-users will have to absorb much of that cost. Because of this, the price structure of your end product could be prohibitive and reduce the customer base that can access your services.

Are there examples of free Text Analysis APIs?

  1. Text Analysis
  2. Google Translate
  3. Lingua Robot
  4. Sentiment Analysis
  5. Word Dictionary
  6. GrammarBot
  7. Rewriter/Paraphraser/T Changer (Multi Language)
  8. Paraphrasing Tool
  9. Twinword Text Analysis Bundle
  10. TLDR Text Analysis


All IMDb APIs are supported and made available in multiple developer programming languages and SDKs including:

  1. Node.js
  2. PHP
  3. Python
  4. Ruby
  5. Objective-C
  6. Java (Android)
  7. C# (.NET)
  8. cURL

Just select your preference from any API endpoints page.

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