Text mining: what it is, methods and how to use it

Text mining is one of the most important methods for analyzing and processing unstructured data, which accounts for almost 80% of the world's data. Today, most organizations and institutions collect and store huge amounts of data in data warehouses and the cloud.

This data grows exponentially every minute as new data is added from many different sources.

As a result, it is difficult for companies and organizations to store, manage and analyse large amounts of text data using traditional techniques. Improving your data mining skills will help you overcome these hurdles.

This article looks at text mining, its methods and its application in business.

What is text mining?

Text mining is the process of extracting important information from text data written in standard language. This information comes from general language text messages, emails and files. It is mainly used to find valuable information from large amounts of data.

It is also a multidisciplinary field that uses information retrieval, data mining, machine learning, statistics and computational linguistics. It refers to the storage of natural language texts in unstructured or semi-structured formats.

In its most basic form, text mining searches for facts, relationships, and validation from large amounts of unstructured text data. This extracted data is then translated into a structured format that can be immediately examined or viewed using HTML tables, mind maps, diagrams, etc. For this purpose, various methods are used to process the text.

Text mining methods

There are different methods and strategies for text mining. They are divided into two areas.

• Basic method
• Advanced method

In this section we will discuss some of the most common methods. First we will discuss the basic methods:

Word frequency

Word frequency can be used to determine which terms or concepts occur most frequently in a data set. When examining customer reviews, social media conversations, or customer comments, it can be useful to find out which words are used most often.

For example, if customer comments include words like expensive and overpriced, that could mean you need to change your pricing (or your target audience).

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A group of words that frequently appear together is called a collocation. The most common collocations are bigrams and trigrams. Bigrams are two words that often appear together, such as B. get going, save time or make decisions (a combination of three words, such as within walking distance or keep in touch).

Finding collocations and counting them as one word allows you to:

• Improve the granularity of the text.
• to better understand its semantic structure
• to get more accurate text mining results.

Konkordanz

Concordance determines where or when a word or group of words occurs 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 up the concordance of a word, one can determine its meaning depending on its usage.

We will now advanced text mining methods to discuss:

Text classification

Text classification is the process of categorizing (labeling) unstructured text data. This essential task of natural language processing (NLP) facilitates the organization and structuring of complex texts into meaningful data.

Text classification allows companies to quickly and cost-effectively analyse all types of information, from emails to support tickets, to uncover valuable insights.

Below we look at some of the most common text classification tasks: topic analysis, sentiment analysis, speech recognition, and intent recognition.

Thematic analysis

Text mining helps understand the main themes of a text and is one of the most common methods of organizing text data. For example, a support ticket that says my online order didn't arrive can be classified as a shipping issue.

You can use the QuestionPro survey software for topic analysis. With QuestionPro you can automatically analyse answers to survey questions and identify the main topics that resonate with respondents.

This allows you to find out what your customers want and need, which helps you make better business decisions and increase customer satisfaction.

Sentiment analysis

Sentiment analysis is one of the most important methods of text mining. The mood underlying a particular text is examined.

Let's say you're looking at a bunch of comments on your website. You may notice that UI-UX or usability appears more frequently in these reviews, but you need more information to draw conclusions.

Sentiment analysis helps you find out what a text is about, what it means and whether it is positive, negative or neutral. Sentiment analysis is a useful business tool that can be used for many different purposes, such as: B. to read reviews or support tickets or to see what people are saying on social media.

QuestionPro is a fully featured survey software with versatile features including sentiment analysis. If you are looking for sentiment analysis tools for your business, QuestionPro is definitely your best choice.

QuestionPro's sentiment analysis tool allows you to automatically analyse survey responses and determine the overall sentiment (positive, negative or neutral) of respondents' answers.

This can help you make business decisions and improve customer satisfaction. It also allows you to quickly and easily identify trends and patterns in customer responses.

Language recognition

One of the best ways to use text mining is to automatically route support requests to the right team based on language. This task is easy to automate and saves teams valuable time. It allows you to classify a text based on language.

Intent detection

You can use a text classifier to automatically figure out what a text is supposed to say or why it was written. This can be very useful when you want to find out what customers are saying.

For example, you can classify replies to outbound sales emails to find out which prospects are interested in your product and which want to unsubscribe.

Text mining

Text mining is a method of text analysis that extracts specific data from texts, e.g. E.g., keywords, company names, addresses, emails, etc. By using text mining, companies can avoid the tedious task of manually sorting through their data to extract important information.

Below we will discuss some of the most important parts of text extraction: keyword extraction, named entity recognition, and feature extraction.

Keyword extraction

Keywords are the most important elements of a text and can be used to analyse its content. Using a keyword extractor makes it possible, among other things, to index searchable data, summarize the content of a text, and create tag clouds.

Named entity recognition

Allows you to find and extract names of companies, organizations or people from a text.

Feature extraction

Helps determine specific characteristics of a product or service in a data set. If you e.g. For example, if you are looking for details of a product, it would be easy to extract details like color, brand, model, etc.

How to use text mining?

Using text mining software can be very useful for companies. They can provide useful information and help grow business intelligence in every industry imaginable. In business, a data mining API is often used for the following purposes:

Reputation Management

A company's public image must be impeccable in today's modern culture. Text mining helps you understand social media listening and Voice of the Customer (VoC) data by analyzing tweets, comments, messages, and other comments related to or related to the company.

This includes company leaders, investors, political parties and groups the company supports, as well as employees and partners. Companies can improve their reputation in real time by taking preventative measures.

Search Engine optimization

Search engines like Bing and Google use text mining to detect spam and filler text on content marketing websites.

The search engine may flag an email as spam based on spelling, context, and intent, or penalize a company website that has been stuffed with keywords to improve its search rankings. 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 historical and current data is critical in medical treatments and clinical trials, new product development, real estate planning, and other areas where big money is made and time is of the essence.

Text analytics allows companies to examine patterns in data for a variety of purposes, including customer behavior. Patterns and trends can also be useful for developing new security and surveillance measures, as well as traffic regulations to ease congestion on busy roads and immigration policy.

Surveys and reviews

Whether through social media reviews, emails, or market surveys, an intelligent text analytics API can identify and classify topics and content.

A text analytics solution leverages techniques such as natural language processing (NLP) and aspect-based sentiment analysis to ensure that all aspects and topics are considered in a single assessment. This case study shows how surveys can be used more effectively with text mining.

Contact QuestionPro, for conducting surveys. QuestionPro has versatile survey functions with ready-made templates. With the advanced features you can also customize the design of your survey.

Employee survey and recruitment

Text mining can help you find the best candidate for a job. You can search through thousands of records in a hiring database using keyword analysis to find the right candidate. You can significantly reduce employee turnover by ensuring your best employees are happy with their jobs.

The use of Voice of Employee (VoE) feedback programs, such as B. Voice, chat and video platforms throughout the employee career can provide valuable information to create an enriching work environment and strong engagement between employee and employer.

Conclusion

Text mining is an effective tool for identifying trends and insights in text data and has many applications. It can be improved by combining it with other techniques such as natural language processing and machine learning.

Overall, text mining is an important tool for extracting information from text data that can be used to make decisions and improve business results.

Now is the time to use text mining in your business. If you need help, QuestionPro is here for you. QuestionPro is a fully featured survey software with great features. It allows you to conduct surveys to get feedback from your customers and employees.

You can also analyse your business data with QuestionPro's text analysis feature. Contact us for a demo or free trial.

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KEYWORDS OF THIS BLOG POST

Text mining | text  | Mining