Helen Gerardia. BLUE CONSTELLATION. 1965-1975. Taubman Museum of Art.

Text analysis informs decision-making across a broad swath of industries and domains. Organizations and businesses leverage text analysis to extract meaningful information from a range of texts including customer reviews, social media posts, and support tickets. Researchers use text analysis to find critical information quickly. Text analysis enables automated content categorization for organizing and understanding large document collections, creating new insights relevant to any subject domain.

We previously introduced the basics of text analysis and why it’s important. In this post, we’ll highlight some of the real-world applications of text analysis and how they inform data-driven decisions.

Text analysis and NLP

First, it’s helpful to know that natural language processing (NLP)—the computational study of human language—is a critical skill for efficiently and effectively analyzing text and speech data. Primary NLP techniques include text classification, named entity recognition, and sentiment analysis.

  • Text classification, aka text tagging or text categorization, is the process of categorizing text into organized groups.
  • Named entity recognition (NER) gives machines the ability to automatically identify or extract entities, like product names, events, and locations. Search engines use NER to understand queries. NER helps chatbots interact with humans. By using NER, teams can automate tedious research tasks.
  • Sentiment analysis is a machine learning technique used to determine whether a given text is positive, negative, or neutral.

Business and academic applications

In business, these tools and techniques enable companies to surface insights, patterns, and trends from large volumes of unstructured data.This ability to set aside all non-relevant material while revealing only pertinent data has led organizations to quickly adopt text analysis for risk and knowledge management, cybercrime prevention, enhanced customer service, claims investigations, contextual advertising, business intelligence, content enrichment, spam filtering, social media data analysis, and much more.

For scholars, librarians, and students, it may not be immediately obvious why text analysis matters, but it does. Today, digital data has become the primary publishing and archival format for humankind. The ability to search and manipulate that record is what will allow future researchers to find important information. Historians of the future looking at our present moment will need to be able to analyze emails, text messages, websites, and other digital files. The ability to search, read, and interpret the cultural record is essential for all research domains. Text analysis is a digital literacy skill that can bring additional evidence to bear on any research topic.

Generative AI and Natural Language Processing

NLP is highly effective in any domain where information is (not surprisingly), collected as text. Think insurance claims, legal and financial documents, scientific literature—including clinical data—that would normally take humans hours to read, understand, and process. NLP techniques can help quickly locate specific information. Generative AI—artificial intelligence systems capable of generating text, images, and other media in response to prompts—is a major shift. By combining machine learning and natural language processing, generative AI can comprehend, generate, and interpret human-like text. Because generative AI can consider the context of words, the meaning behind them, and grasp the subtleties of language, it is able to explore deeper levels of insight from the same data sets.

A few decades ago, business insights data could only be analyzed by trained, specialized professionals. Today, digital data is the main record for society. Even small businesses often have more data than they have the expertise to understand and implement. The ability to search and manipulate digital records, to clean and connect them, has become essential for decision making, from the C-suite to middle management. Today, the vast majority of data in any business is unstructured text, including internal email, user feedback, social media, and transaction data. This quickly becomes a difficult-to-manage firehose of information for researchers without text analysis skills.

Become data literate

You don’t need to be a data scientist to benefit from text analysis, but you do need to understand a programming language like Python or R. The good news is that programming and text analysis, like any skill, can be learned. To get started, check out the Text Analysis Pedagogy (TAP) Institute. First offered in 2021 in partnership with the National Endowment for the Humanities, the TAP Institute sought to address the humanities’ needs for greater community support, technical infrastructure, and open educational resources by offering a free series of events and classes for anyone interested in teaching text analysis.

TAP Institute works in partnership with Constellate, part of ITHAKA’s portfolio of nonprofit services aligned around a shared mission to improve access to knowledge. Constellate is the only text analysis platform that integrates access to scholarly content and open educational resources into a cloud-based lab to help faculty more easily and effectively teach text analysis and data skills. With Constellate, learners across all disciplines can apply text analysis methods to datasets, and hone their skills with support from on-demand tutorials, live classes taught by experts, and engagement with an inspiring user community.

TAP Institute courses are taught using Constellate and are designed to be progressive, so you will benefit from taking a single course or the entire series, no matter your skill level. Taught by leading text-analysis experts, these free courses are designed as open educational resources for a collaborative community of librarians and instructors.

Constellate also offers Python intensives every quarter, and asynchronous video courses on demand. Visit our site and our classes and events page for details. Please reach out to sign up for a Constellate trial, or contact us with any questions you might have about text analysis, Constellate, or the TAP Institute.

Text analysis proficiency is critical to making data-driven decisions. It can help turn unstructured data into structured data, but it can also help make unstructured textual data actionable. If you haven’t already, now is the time to improve your data literacy. ITHAKA, Constellate, and the TAP Institute are here to support you on your path to success in this digital age.