Look Who's Talking: Bipartite Networks as Representations of a Topic Model of New Zealand Parliamentary Speeches

Quantitative methods to measure the participation to parliamentary debate and discourse of elected Members of Parliament (MPs) and the parties they belong to are lacking. This is an exploratory study in which we propose the development of a new approach for a quantitative analysis of such participation. We utilize the New Zealand government’s digital Hansard database to construct a topic model of parliamentary speeches consisting of nearly 40 million words in the period 2003-2016. A Latent Dirichlet Allocation topic model is implemented in order to reveal the thematic structure of our set of documents. This generative statistical model enables the detection of major themes or topics that are publicly discussed in the New Zealand parliament, as well as permitting their classification by MP. Information on topic proportions is subsequently analyzed using a combination of statistical methods. We observe patterns arising from time-series analysis of topic frequencies which can be related to specific social, economic and legislative events. We then construct a