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Content analysis is the study of documents and communication artifacts, known as texts e.g. photos, speeches or essays. Social scientists use content analysis to examine patterns in communication in a replicable and systematic manner. [1]
Online content analysis or online textual analysis refers to a collection of research techniques used to describe and make inferences about online material through systematic coding and interpretation. Online content analysis is a form of content analysis for analysis of Internet-based communication.
A content audit is "an accounting of all currently published web content" [1] and a "cornerstone of content strategy". [2] It is a qualitative analysis of information assets on a website; that is, the assessment of content and its relationship to surrounding information assets within specified website content analysis parameters.
A content inventory is the process and the result of cataloging the entire contents of a website. An allied practice—a content audit—is the process of evaluating that content. [1] [2] [3] A content inventory and a content audit are closely related concepts, and they are often conducted in tandem.
Mathematica – provides built in tools for text alignment, pattern matching, clustering and semantic analysis. See Wolfram Language, the programming language of Mathematica. MATLAB offers Text Analytics Toolbox for importing text data, converting it to numeric form for use in machine and deep learning, sentiment analysis and classification ...
The automation of content analysis has allowed a "big data" revolution to take place in that field, with studies in social media and newspaper content that include millions of news items. Gender bias, readability, content similarity, reader preferences, and even mood have been analyzed based on text mining methods over millions of documents.
Frame analysis (also called framing analysis) is a multi-disciplinary social science research method used to analyze how people understand situations and activities. Frame analysis looks at images, stereotypes, metaphors, actors, messages, and more. It examines how important these factors are and how and why they are chosen. [1]
Coding reliability [4] [2] approaches have the longest history and are often little different from qualitative content analysis. As the name suggests they prioritise the measurement of coding reliability through the use of structured and fixed code books, the use of multiple coders who work independently to apply the code book to the data, the measurement of inter-rater reliability or inter ...
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