10 Text & Sentiment Analysis APIs
Want to write better content (for your users + Google)?
Consider using text analysis tools.
Doing some advanced entity based keyword research can be a great way to understand what Google expects to see in the results. And then create exactly that.
Things can get complicated quickly here. And there’s quite a few abbreviations in this space, like even more than in the SEO space.
Here’s the ones you need to know (for a basic understanding):
- NLP – natural language processing
- AI – artificial intelligence
- NER – named entity recognition
- LSI – latent semantic indexing
Check out these text analysis APIs (+ documentation):
IBM Watson API
IBM Watson API uses the power of artificial intelligence and a sophisticated analytical software to understand and process text as a “question answering” machine.
Google Cloud Natural Language API
Google Cloud Natural Language API is an advanced language processing NLP tool.
It can analyze text with AI using pre-trained or custom machine learning models to extract relevant entities, understand sentiment, and more.
Repustate is a simple to use API for sentiment analysis and text analytics. It can analyze text in multiple languages for sentiment and semantic insights.
TextRazor is a fast Natural Language Processing API used for entity extraction, keyphrase extraction, automatic topic tagging and classification (in 12 languages).
Text APIs by ParallelDots
ParallelDots Text APIs is one other collection of several text analysis and data generation tools built into one useful package any website administrator will find incredibly useful (and additionally easy to integrate).
Feed it any data or document that you need to have looked at by the system and it gets back to you with intuitive data extracted from your input.
Microsoft Text Analytics API
Microsoft Text Analytics API turns unstructured text into insights like sentiment analysis, key phrase extraction, and language and entity detection.
Aylien API is a package of information retrieval, machine learning and NLP APIs for analyzing text content at scale. It can extract insights and meaning from documents, tweets, URLs, news articles, and more.
Twinword APIs is a language analysis API for building tools and applications that analyze and understand natural human text.
It provides a range of useful applications for SEO such as:
- Sentiment & Emotion Analysis – Is this comment positive or negative?
- Topic Tagging – Automatically generate topics and keywords for articles and blogs.
- Text Classification – Suggest related categories for each blog, article, or post.
- Keyword Suggestion – Get a list of keyword suggestions scored by relevance for SEO and SEM campaigns.
MonkeyLearn is a text analysis and machine learning API that can classify, extract, or manage custom models programmatically.
You can train custom machine learning models to get topic, sentiment, intent, keywords and more right inside Google Sheets.
Frase is a useful text analysis tool to help content marketers speed up content research by automatically summarising text. You can use this API to extract 15+ structured data points from a URL (such as clean text, topic extraction, summarisation, category classification and more).
Machine learning for marketing (briefly) explained
Machine learning machine learning (ML) is helping humans solve problems in a more efficient way.
Text and sentiment analysis are two related methods that are useful for marketers.
Here’s a quick definition for each:
What is text analysis?
A big portion of the internet is
cat pictures text content. Everything from instant messages, blog comments, articles, reddit posts and so on.
Text analysis takes those texts and allows you to automatically extract and classify information from text content.
Anything text based can be analyzed. Things like tweets, emails, support tickets, product reviews, and survey responses and more to provide information like keywords, geographical information, SEO statistics or sentiment.
What is sentiment analysis?
Sentiment analysis is a more advanced form of text analysis API.It is the interpretation and classification of emotions (positive, negative and neutral) in text..
Using sentiment analysis allows you to identify customer sentiment (feelings) toward products, brands or services by taking their online conversations and feedback.
Instead of just looking for things like keyword topics, sentiment analysis goes a little deeper and is able to tell you exactly how users may feel towards a thing.
Semantic text analysis & natural language APIs for marketers
Think I’ve missed a text analysis API? Just let me know and I’ll add it.