Text mining is one of the most important methods of analyzing and processing unstructured data, which accounts for almost 80% of the world’s data. Most organizations and institutions today collect and store huge amounts of data in data warehouses and the cloud.
This data continues to grow exponentially every minute as new data comes in from many different sources.
As a result, it is difficult for businesses and organizations to store, handle, and analyze massive amounts of textual data using traditional techniques. Upskilling with data mining will assist you in overcoming the obstacles.
This blog will discuss text mining, its methods, and how to use it in business. Let’s jump into it.
What is Text Mining?
Text mining is the process of getting important information from text data written in standard language. This information comes from common language text messages, emails, and files. It is mostly used to find valuable insights from large amounts of data collection.
It is also a multidisciplinary field that uses information retrieval, data mining, machine learning, statistics, and computational linguistics. It relates to storing natural language text in unstructured or semi-structured formats.
Text mining, in its most basic form, seeks facts, relationships, and validation from large amounts of unstructured textual data. This extracted data is then translated into a structured format that can be studied or shown immediately using HTML tables, mind maps, charts, etc. It uses a variety of approaches to process the text for this purpose.
Effective Methods of Text Mining
There are various methods and strategies for text mining. They are divided into two parts.
- Basic method
- Advance method
We will talk about some of the most common methods in this section. At first, we will go for basic methods:
- Word Frequency
Word frequency can be used to determine which terms or concepts appear most frequently in a set of data. When looking at customer reviews, social media conversations, or customer feedback, it can be helpful to find out which words are used the most.
For example, if your customer reviews are full of words like expensive, overpriced, and overrated, that could mean you need to change your prices (or your target market).
- Collocation
A group of words that commonly appear together is known as a collocation. Bigrams and trigrams are the most common types of collocations. Bigrams are two words that usually go together, like get started, save time, or decision-making (a combination of three words, like within walking distance or keep in touch).
Finding collocations and counting them as one word allows you:
- Improve the text’s granularity
- Understand its semantic structure better
- Get more accurate results from text mining.
- Concordance
Concordance determines where or when a word or group of words appears in a sentence or text. We all know that words can have more than one meaning and that the same word can be used in many different ways. By looking at a word’s concordance, you can determine what it means based on what it is used for.
Now we will discuss advanced methods of text mining:
- Text Classification
Text classification is the process of categorizing (tagging) unstructured text data. This essential task of Natural Language Processing (NLP) makes it easy to organize and structure complex text into meaningful data.
Text classification lets businesses quickly and cheaply analyze all kinds of information, from emails to support tickets, to gain valuable insights.
Below, we will discuss some of the most common tasks for text classification: topic analysis, sentiment analysis, language detection, and intent detection.
- Topic Analysis
Text mining aids in understanding a text’s main themes or subjects and is one of the most common methods of organizing text data. For example, a support ticket stating that my online order has not arrived can be classified as a shipping issue.
You can utilize QuestionPro survey software for topic analysis. With QuestionPro, you can automatically analyze responses to survey questions and identify the main topics that respondents are discussing.
It can help you figure out what your customers want and need, which can help you make better business decisions and make your customers happier.
- Sentiment Analysis
Sentiment analysis is one of the most important methods of text mining. It entails examining the feelings that underlie any given text.
Assume you are looking at a series of reviews for your website. You might find that UI-UX or Ease of Use comes up most often in those reviews, but you need more information to draw any conclusions.
Sentiment analysis helps you figure out what a text is about, what it means, and whether it is positive, negative, or neutral. Sentiment analysis is a helpful business tool that can be used for many different things, like reading reviews or support tickets or looking at what people say on social media.
QuestionPro is a complete survey software with versatile features, and sentiment analysis is one of them. If you are looking for sentiment analysis tools for your business, QuestionPro is undoubtedly the best option for you.
With QuestionPro, you can use their sentiment analysis tool to automatically analyze survey responses and determine the overall sentiment (positive, negative, or neutral) of the respondent’s answers.
They can help you make business decisions and improve customer satisfaction. It can also help you find trends and patterns in customer feedback quickly and easily.
- Language Detection
One of the best things text mining can do is automatically send support tickets to the right team based on their language. This task is easy to automate, which saves valuable time for teams. It allows you to classify a text based on its language.
- Intent Detection
You could use a text classifier to automatically figure out what a text is trying to say or why it was written. It can be very helpful when trying to figure out what customers say.
For example, you could sort outbound sales email responses to find potentials who are interested in your product and those who want to unsubscribe.
- Text Extraction
Text extraction is a text analytical method that extracts specific data from a text, such as keywords, entity names, addresses, emails, and so on. By using text extraction, businesses can avoid the trouble of manually sorting through their data to pull out important information.
Below, we will talk about some of the most important parts of text extraction: keyword extraction, named entity recognition, and feature extraction.
- Keyword Extraction
Keywords are the most significant elements in a text and can be used to analyze its content. Using a keyword extractor allows you to index searchable data, summarize text content, and create tag clouds, among other things.
- Named Entity Recognition
It enables you to locate and extract the names of businesses, organizations, or people from a text.
- Feature Extraction
It assists in determining specific features of a product or service in a set of data. For example, if you were looking at product details, it would be easy to pull out details like color, brand, model, etc.
How to Use Text Mining in Business?
Utilizing text mining software can be very beneficial for businesses. They can give helpful information and help business intelligence grow in any industry you can think of. In business, a data mining API is often used in the following ways:
- Reputation Management
A company’s public image must be flawless in today’s modern culture. Text mining helps you understand social media listening and voice of customer (VoC) data by analyzing tweets, comments, news stories, and other feedback that reference it or anything related to it.
It includes corporation leaders, investors, political parties, and groups that the company supports, as well as employees and partners. Companies can enhance their reputation in real time by implementing preventative actions.
- Search Engine Optimization
Search engines like Bing and Google use text mining to recognize spam and filler text in content marketing websites.
The engine can mark an email as spam based on spelling, context, and intent or penalize a company website that has been keyword stuffing to boost its search ranking. A text analytics API can also be used to optimize and strengthen a company’s own search engine.
- Finding Patterns in Data
Finding patterns in data, both historical and current is a critical aspect in medical treatments and clinical trials, new product development, real estate planning, and other highly monetized and time-sensitive areas.
Text analytics enables businesses to investigate data patterns for various purposes, including customer behavior. Patterns and trends can also be useful in developing new policies for security and surveillance, as well as traffic regulations to alleviate congestion on high-traffic routes and immigration policies.
- Surveys & Reviews
Whether it is through reviews on social media, emails, or market research surveys, a smart text analytics API can recognize and classify topics and themes.
A text analytic solution employs techniques such as natural language processing (NLP) and aspect-based sentiment analysis to ensure that all aspects and themes are considered in a single review. This case study shows how surveys are used most effectively with text mining.
Contact with QuestionPro to conduct surveys. QuestionPro has versatile survey features with ready templates. You can also customize your survey design with their advanced features.
- Voice of the Employee & Recruitment
Text mining can help you find the best candidate for the job. It can search through thousands of records in a recruitment database using keyword analysis to find the right candidate. You can significantly reduce employee attrition by ensuring your star employees are happy at work.
Using voice-of-the-employee (VoE) feedback programs, such as voice, chat, and video platforms, throughout the employee journey can provide valuable insights into creating a nurturing work environment and deep employee-employer engagement.
LEARN ABOUT: Data Mining Techniques
Conclusion
Text mining is an effective tool for identifying trends and insights in text data and has many applications. It can be enhanced by combining it with other techniques, such as natural language processing and machine learning.
Overall, it is an important tool for extracting insights from text data that can be used to inform decision-making and improve business outcomes.
Now it’s time to utilize text mining in your business. If you need any help, QuestionPro is there for you. QuestionPro is a complete survey software with excellent features. We allow you to conduct surveys to know your customer and employee feedback.
You can also analyze your business data with the text analysis feature of QuestionPro. So without wasting your time, Contact QuestionPro for a free trial.
