Literata

Hours: ~30. Produced: 2010.

Literata is a Vocabulary Analysis Tool. It is used to compare the vocabulary richness of two or more texts. I created it because I like writing; I see it as one of my biggest hobbies. And because I like writing, I begun work at my first book in 2010, during the NaNoWriMo literary marathon. Although I liked how the book was shaping up, I felt unsure about the richness of my vocabulary, since English is not my mother tongue. Thus, Literata was born.

Literata Text Input Window

The purpose of Literata is simply to show somebody how their vocabulary measures up in relation with others, or even one’s previous works. For example, two earlier works can be compared with a newer work. In this case, Literata should be able to make one strive for a better, more extensive use of the vocabulary.

Literata is one of my smaller projects. Since it’s (very) niche, I didn’t continue development past version 0.1, due to time constraints.

Literata is Open Source Software, available under the GPL license. It can be downloaded here^ or you can visit its SourceForge page^.

Technical Aspects

On the technical side, DevExpress controls are used to enhance the functionality and graphical aspect of the Application. The greatest advantage taken from using DevExpress is the nice charts which I was able to create.

Literata New Words Chart

Literata employs simple threading during text analysis, which is quite fast. The Application does not save the text it analyzes, only the results. However, as part of the results, new words in the text are indeed saved.

Literata Recorded Results Window

It uses a few of my standard C# practices such as: binary serialization of the settings file and saving window position & state between sessions (laugh all you want, but huge names manage to mess this up, and I feel very strongly about this basic feature).

Other Aspects

The Application comes with several pre-defined Analysis Results created with it, based on the work of other authors (such as Kafka, Herbert, Pratchett), which can be used to start comparisons as soon as its installed. These results have been extracted from the English versions of those books. In case the user’s language is NOT English, Literata can still be used, but the user should add some reference works written in the targeted language, to serve as a base for comparisons. The longer the text is, the more accurate the results are. Recommended text size is between 50k words and 200k words.

Of course, vocabulary and “new words count” are NOT what makes a work stand out. It’s just a number. But it’s a number that COULD, indicate problems. For example, that the user’s vocabulary is too narrow, words are repeated too often, etc..