What is content analysis?
Philipp Mayring, Austrian psychologist, professor, and renowned qualitative researcher offers an authoritative, but rather academic discussion of content analysis. What does it really mean? Content analysis is our bread and butter here at Quantified Communications, and we thought it was time we put together an accessible overview of what we’re talking about when we talk about content analysis.
What is content analysis?
Content analysis is a systematic approach to building an objective interpretation of almost any kind of content. The method can be applied to text, video, online content, spoken communications… essentially, anything that can be recorded for later review. Analysts can use the process to target format, content, or both.
Format: Length of sample, ratio of visuals to text, bullet points vs. paragraphs, etc.
Content: Tone, themes, sentiment and emotions, target audience, etc.
The outcome is a quantified breakdown of the key elements of your communication sample. Content analysis aims to bring scientific credibility to the more subjective text analysis you might have practiced in your college literature classes and research papers.
How does content analysis work?
At a very basic level, content analysis requires three steps:
- Create analysis categories: based on your reading of the text, identify the thematic, structural, or linguistic elements you want to analyze. For example, confident language, finance-related subject matter, or 2nd person point of view.
- Identify the unit of measurement: determine whether you’ll be counting by word, sentence, or paragraph within the text.
- Count the instances of language that falls into each category to determine just how strong these elements truly are within the text.
(To learn more about the process, visit UC Davis’ Introduction to Content Analysis.)
Historically, content analysis was a manual process. Analysts would go through texts by hand, counting the number of words that matched each category. As you might imagine, the process was slow and inefficient—it was nearly impossible to obtain an accurate analysis of large samples of content.
However, as technology has developed, content analysis has become much more efficient and sophisticated. We can now leverage advances in data science and natural language processing to analyze large quantities of content, mining data on key themes and linguistic markers, comparing samples to similar content, and creating improvement plans to ensure your content is as effective as possible.
To find out how Quantified Communications can use content analysis to help you improve your organization’s communication strategy, email us at info@quantifiedcommunications.com.
More on content analysis from Quantified Communications.