ONLINE LECTURE> Friday 14 May at 10am UK time, Chris Handy, "Historical Politeness and Digital Humanities: Computing Buddhist Politeness: Etiquette Algorithms for Sanskrit, Tibetan and Chinese"

Christopher Handy's picture
Historical Politeness Network for Ancient Languages: Online lecture Series (Spring 2021)
 
Dear Colleagues,
 
The Historical Politeness Network for Ancient Languages would like to invite you to join us for our new virtual lecture series showcasing the latest research on historical politeness in ancient languages (this semester we will cover ancient Egyptian, ancient Greek, Latin and Sanskrit). All lectures will take place using Zoom.
 
To register, please email Dr Maria Tsimpiri (M.Tsimpiri@uea.ac.uk)
 
Our next virtual lecture is:
Friday 14 May at 10am UK time
Historical Politeness and Digital Humanities: Computing Buddhist Politeness: Etiquette Algorithms for Sanskrit, Tibetan and Chinese
Chris Handy (Leiden University, The Netherlands)
 
Abstract:
This presentation focuses on computational techniques for locating something called politeness or etiquette in classical Buddhist texts composed in Sanskrit, Chinese, Tibetan and related languages. My basic argument is that while politeness itself remains an ambiguous and contested term, we can nevertheless extract useful information about texts and themes related to the concept of politeness through simple statistical analysis techniques. I focus on three major languages of the Buddhist tradition in order to illustrate some issues relating to my own research content, but the ideas here could also be extended to any languages. Beginning with an overview of the general problems involved in attempting to quantify the concept of politeness, I provide examples from Buddhist texts to illustrate common obstacles to achieving that goal. Then, I show the results of a few small computational experiments on these languages.
In the second part of the talk, I describe the components of the custom software I create for these language experiments, and how to build a complete web-based language analysis app for similar tasks in any language using Python and Django.
 
Hope to see you there!