Word frequencies and counts are text analysis methods that return results about the words in a text or set of texts. Counts return the amount of times a word is used in the text, whereas frequencies give a sense of how often a word is used in comparison to others in the text.
This section presents a concise summary of what the recipe will teach, focusing primarily on: (1) the outcome of the recipe (what are you trying to achieve, in non-technical terms); (2) the main technical approaches employed; and (3) whether the recipe is based on someone else’s work/code (they should be cited if so).
This is a recipe for looking at the changes that have taken place in a wikipedia article over time, and generating a corpus of the different edited versions.
This recipe will guide you in developing a digital archival file collection suitable for deposit in an academic institution’s digital archive, including descriptive XML metadata documentation and a readme document.
This recipe is a guide to developing a detailed summary for text analysis or other research-oriented tools, based on primary and secondary sources. It is particularly useful for providing information on legacy tools that are no longer available, but is also extensible to modern tools.
This recipe is a guide to developing a review for a text analysis tool that will enable other users to decide whether that tool is suitable for their research tasks.
This recipe extracts information about perceived social networks from a text populated with references to individuals.
This recipe uses text analysis tools for Collocation, List Words and Concordance to extract key words and create an index and table of contents from a body of text.
This recipe uses Frequency lists and an Aggregate Text tool to build meta tags for a web page or website.