A Corpus of Argument Networks: Using Graph Properties to Analyse Divisive Issues

Barbara Konat, John Lawrence, Joonsuk Park, Katarzyna Budzynska, Chris Reed

Abstract:

Governments are increasingly utilising online platforms in order to engage with, and ascertain the opinions of, their citizens. Whilst policy
makers could potentially benefit from such enormous feedback from society, they first face the challenge of making sense out of the large
volumes of data produced. This creates a demand for tools and technologies which will enable governments to quickly and thoroughly
digest the points being made and to respond accordingly. By determining the argumentative and dialogical structures contained within
a debate, we are able to determine the issues which are divisive and those which attract agreement. This paper proposes a method of
graph-based analytics which uses properties of graphs representing networks of arguments pro- & con- in order to automatically analyse
issues which divide citizens about new regulations. By future application of the most recent advances in argument mining, the results
reported here will have a chance to scale up to enable sense-making of the vast amount of feedback received from citizens on directions
that policy should take