Text mining software helps businesses analyze text data about their brand, whether social media conversations, online reviews, emails, and more.
Using powerful text mining software, you can monitor sentiment and public perception about your products or services, and gain valuable insights that help inform business decisions.
When you decide to implement text mining tools, you'll need to ask yourself whether you want to build or buy a text mining solution.
If you’re an experienced coder, you might decide to build text analysis software using open-source tools like Keatext, KNIME, and Refinitiv. However, you’ll need a team of data scientists and developers, as well as robust infrastructure, which means you’ll also need high capital expenditure.
SaaS text mining software is more useful for companies that don’t want to spend months building tools from scratch or incur huge upfront costs on hiring staff and the infrastructure itself.
In summary, you have two options:
Read on for a comparison of the best text mining solutions on the market.
The 7 best online text mining tools to analyze text like a pro:
Best for: Companies looking for SaaS text analysis software that’s user-friendly, highly customizable, and easy to integrate with existing tools.
MonkeyLearn is a powerful text mining tool for analyzing all of your documents, survey responses, social media, online reviews, customer feedback data – almost any form of unstructured text data for quantitative content analysis.
Advanced machine learning algorithms and natural language processing (NLP) techniques allow the software to read text just like a human would. So you can ensure your analysis will be accurate.
With MonkeyLearn you can upload data directly into the app or easily integrate with Google Sheets, Excel, Zendesk, Zapier, and more. MonkeyLearn’s advanced machine learning makes creating your model painless. And you can connect APIs in all major languages with very little coding.
Try out the pre-trained text extraction and text classification models below, then request a demo to learn how you can get the most out of these tools:
Best for: Companies looking for a managed service and easy integration with Google Cloud Storage.
Google Cloud NLP (natural language processing) is a great option for companies that already store data on Google’s cloud and want integration with Google apps.
They offer pre-trained models for sentiment analysis, entity extraction, content classification, and syntax analysis that you can start using right away. Their AutoML Natural Language allows you to train models to your specifications, and their Natural Language API allows developers to call the models with fairly simple code.
Best for: Large companies with staff engineers that want to create hyper-specialized text mining models.
IBM Watson is known for its advanced adaptability to a variety of industries and the ability to build to massive scale across any cloud.
Their technology can be implemented with existing apps and may require more coding expertise, depending on the level of integration.
Watson Speech-to-Text is one of the most advanced options on the market for companies that need to perform text mining on spoken conversations or recorded audio.
Best for: Companies that want managed software, easy installation, and pre-built models.
Amazon Comprehend is wholly managed by Amazon, so there’s no need for private servers. And APIs come pre-trained, although you can create your own text mining models with AutoML.
Comprehend is ideal for companies with low coding abilities that want to use text mining within the applications they already use. You can organize and categorize documents and searches to recommend new subjects and help readers find what they’re looking for.
Best for: Companies that need to analyze international news reports.
AYLIEN’s News API allows you to real-time search and data mine thousands of daily news sources in 16 languages from around the world. They add up to 25 data enrichments to every article to allow for specialized search and filter options: event detection and clustering, category tagging, sentiment analysis, and more.
They also offer a pre-built Text Analysis API, or you can build your own with their Text Analysis Platform. All of which are available in seven major programming languages.
Best for: Companies that need pre-built customer support and customer analytics software.
Thematic integrates easily with existing customer surveys and customer support applications, like SurveyMonkey, Zendesk, Medallia, and more. Or they can pull data from NPS providers or your internal database.
Thematic’s text processing artificial intelligence works to find themes and recurring subjects in feedback data, analyze their impact on your metrics, and present insights and infographics that are clear and easy-to-read.
Best for: Companies that want to train text mining models to the language of their specific industry.
With MeaningCloud you can create custom dictionaries or merge with existing resources (dictionaries, taxonomies, sentiment models, etc.). Their software is ideal for Voice of the Customer analysis and document coding and management.
Their SDKs and plug-ins provide a template that can be modified for precise analysis. Their graphic interface transforms your analysis into digestible insights and allows you to easily customize within the system, without advanced coding knowledge.
There are a variety of text mining tools on the market that can be undeniably helpful to perform named entity extraction, sentiment analysis, keyword extraction, NPS analysis, and more.
Now, it’s just a matter of finding out what’s best for you. What kind of text documents do you need to analyze? Do you need something highly customizable to gain insights from industry-specific text or something super easy to implement?
MonkeyLearn is easy-to-use and can be configured to your specific needs. Request a demo from one of our experts and start data mining like a pro.
May 14th, 2020