About 1

About this Dashboard

Using the literary translation dataset collected and written about by Erlin et al. (2022) in “The TRANSCOMP Dataset of Literary Translations from 120 Languages and a Parallel Collection of English-Language Originals,” we pose the following questions: (1) What are the general trends in this dataset in relation to what languages were translated? (2) Is there a correlation between time and languages in terms of when different languages were translated?

Heatmaps 2

Heat Map

Translations by Language and Time

Heat Map

Correlation between Time translated and Languages

There is indeed a correlation between the language translated from and language translated from. I could only get one of them to show up and it was the weird one.

# Regressions 3 {.storyboard data-width=“1100”}

All Lined Up

###Year of Publication and Number of Translations

Yay for visuals that work, even if they aren’t pretty. The mean number of translations do increase over time but the scatterplot actually shows an interesting trend. For the Translations by language the most common languages are european ones, but the highest bar of the bar graph is actually english. This needs to be removed in the final version.

## More Regressions? {data-width=“500”} ### Translations per Language

Again there are more visuals that “work” but don’t appear. This was another way to visualize the findings in the last column.

Translating Sentence Length 4

Column

Mean Sentence Length by Language

This time we are looking at the average english sentence length of texts that have been translated into English within our sample, seperated by language. There are some strong examples, with an average of 250 characters in one?! Hardly seems accurate.