Analyzing texts – software and tutorials

First, it is important to understand that you do not necessarily need specific software to analyze texts. Sometimes, even if what you are interested in is style, you will be better off creating a “classical” dataset (one row per text, one column per interesting feature of the text) and analyzing it with a spreadsheet editor or classical functions in R, rather than feeding the entire text into specific software (provided that you have the means to digitize it). But sometimes, as we also explain in Chapter 7, you might want to use specific tools devised for texts – the object of this post. Here is a useful, if far from exhaustive, survey of software; we give more details on some options below. Continue reading “Analyzing texts – software and tutorials”

Analyzing texts – structured historical corpora

In Chapter 7, we warn readers against the use of Google Books as a source on the historical use of words: Google Books does not contain everything that has ever been printed; it is biased in many directions (e.g. towards the English language), most of which are unknown. There are, however, corpora, generally built by linguists, that allow you to know inside which group of texts exactly you plot the use of this or that word, or you investigate which words were often used together. You can also choose to restrict your analysis to a part of the corpus (by author, say, or period). Those are also texts that have been checked and indexed by humans: they do not include errors due to optical character recognition and in most cases, they allow an analysis of grammatical categories. The drawback is, of course, that you can only explore what is in the corpus, i.e., often, something like the canon. But anyway, you cannot seriously count if you have not defined a perimeter of what you include and do not include. Continue reading “Analyzing texts – structured historical corpora”