B(eo)W(u)LF: Facilitating recurrence analysis on multi-level language
This work provides a practical tool for researchers in linguistics and discourse analysis to structure and analyze multi-level linguistic data, though it is incremental as it builds on existing data format ideas.
The authors introduced B(eo)W(u)LF, a data format for multi-level language analysis, and developed tools in Python and MATLAB to facilitate recurrence-based discourse analysis, demonstrated on 319 lines of Beowulf translated into modern English.
Discourse analysis may seek to characterize not only the overall composition of a given text but also the dynamic patterns within the data. This technical report introduces a data format intended to facilitate multi-level investigations, which we call the by-word long-form or B(eo)W(u)LF. Inspired by the long-form data format required for mixed-effects modeling, B(eo)W(u)LF structures linguistic data into an expanded matrix encoding any number of researchers-specified markers, making it ideal for recurrence-based analyses. While we do not necessarily claim to be the first to use methods along these lines, we have created a series of tools utilizing Python and MATLAB to enable such discourse analyses and demonstrate them using 319 lines of the Old English epic poem, Beowulf, translated into modern English.