Computer-assisted textual analysis can be instrumental at this point, as it allows you to perform certain tasks automatically (without having to read all the data) and makes it simple to observe patterns and get unexpected insights.
One of the challenges of textual analysis resides in how to turn complex, large-scale data into manageable information.
In short, textual analysis consists of describing the characteristics of a text and making interpretations to answer specific questions. In this case, the purpose of textual analysis is to understand the cultural and ideological aspects that underlie a text and how they are connected with the particular context in which the text has been produced. While similar to text analysis, textual analysis is mainly used in academic research to analyze content related to media and communication studies, popular culture, sociology, and philosophy. Let’s start with the basics! Getting Started With Textual Analysis What is Textual Analysis?
What is computer-assisted textual analysis?. 
Difference between textual analysis and content analysis?. Thanks to algorithms trained with machine learning it is possible to perform a myriad of tasks that involve analyzing text, like topic classification (automatically tagging texts by topic), feature extraction (identifying specific characteristics in a text) and sentiment analysis (recognizing the emotions that underlie a given text).īelow, we’ll dive into textual analysis with machine learning, what it is and how it works, and reveal its most important applications in business and academic research: Whether analyzing data in business or performing academic research, manually reading, analyzing, and tagging text is no longer effective – it’s time-consuming, results are often inaccurate, and the process far from scalable.įortunately, developments in the sub-fields of Artificial Intelligence (AI) like machine learning and natural language processing (NLP) are creating unprecedented opportunities to process and analyze large collections of text data. Textual analysis is the process of gathering and examining qualitative data to understand what it’s about.īut making sense of qualitative information is a major challenge.
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