Text Analysis is a cutting edge technology. Text analytics software is used to efficiently extract information from large amounts of unstructured text data. It digitally extracts useful information from unstructured text, like: web pages, email messages, social media postings, online reviews, tweets, survey results, call center agent notes, and other kinds of written feedback. These types of text cannot easily be mapped using standard database fields.
The field of text analytics exists because unstructured text provides businesses with a valuable source of information. With improvements in artificial intelligence, text analytics has become even more efficient.
The term text mining is roughly the same as text analytics. Text mining is usually used to obtain qualitative information such as using customer surveys to find out if they are happy with your product. Text analytics, on the other hand, provides greater insights like discovering trends in the unstructured data. Text classification is, again, similar in that it categorizes text into organized groups. If you’d like to learn more about various terms used in text analytics conversations, check out A glossary of Big Data terminology.
Text mining is considered legal in the United States, along with South Korea, Israel, Taiwan and other fair-use countries.
Text Analytics Attributes
According to Predictive Analytics Today these are the features of text classification software:
- Text mining, Text parsing, Text identification, Text extraction, Text categorization, Text clustering.
- Extraction of Concepts, entities, relations, events.
- Creation of taxonomies.
- Search access, Web crawling, indexing, duplicate document identification.
- Analyze all major file formats and all major languages natural- Natural Language/Semantic Toolkits.
- Entity relation modeling.
- Link analysis, link text repositories.
- Ability to identify and analyze sentiments, people, places and other information from websites, Internal files, reports, surveys, forms, employee surveys, claims, underwriting notes, medical records, emails, news, blogs, social media, customer surveys, market surveys, online forums, online reviews, review sites, scientific journals, website feedback, call center logs, transcripts, snail mail, sales notes.
- Document summarization features and records management.
- Interactive visualization.
If you are not sure which text analytics software will fit your needs, we highly recommend this comprehensive publication, 23 Text Classification Tools Compared. To obtain a no-cost report that reflects what you want in a text analytics tool, simply fill out our custom text classification survey.
Industries that Use Text Analytics
Text analytics has many applications including:
- Biomedical applications
- Security applications
- Sentiment analysis
- Online media applications
- Software applications
- Mining scientific literature
- Computational sociology; Digital Humanities
- Marketing and business applications
With so many applications, it’s no wonder that industries are tapping into this resource called text analytics. These industries include:
Surveillance agencies: For example the US Department of Homeland Security reportedly uses text analytics to check social media sites for any sign of terrorist activity.
Hospitality: Gain deep insights from analyzing customer reviews to see what they are doing right and where they stand to improve.
Medical / pharmaceutical companies: For example, performing scheduled evaluations to check for safety issues in published literature; Improving efficiency of document processes, tracking, and other activities.
Public Relations / Advertising: Text analytics is excellent at sentiment analysis. Customer views can be tracked in real-time, giving PR personnel an early warning of trouble.
Retail: Customer support centers benefit from text analytics organizing and analyzing customer feedback to find customer “pain points” and improve their processes.
Research institutes: Solutions for changing the process of obtaining knowledge from unstructured text. In turn, these insights are used as building blocks for future research tasks.
Financial services: Instead of manually searching many legal documents, staff are using Natural language processing-based text analytics solutions to easily search for phrases that relate to finance or fraud.
Wikipedia states “The term text analytics describes a set of linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources for business intelligence, exploratory data analysis, research, or investigation.”
A very large percentage of business data comes in the form of text. It makes sense for businesses who are looking to gain valuable insights, to make use of the advancements in text analytics. Doakio can be your partner in the search for effective text analytics software. Many industries are already reaping the rewards from this exciting new technology.