Gaining Greater Insights from Public Consultations with Data Science & NLP

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Public consultations give people of all backgrounds an opportunity to get involved in government policy making. However, the analysis of large amounts of free-text responses from the public can be time consuming and challenging.  We believe increasing the use of data science and natural language processing techniques can help gain greater insights into the public responses to policy questions, while at the same time reducing the strain on government departments by eliminating resource intensive, manual analyses.

Introduction

Ongoing dialogue between the government and the public is a vital part of the policy-making process. Sometimes this takes place via roundtables with expert stakeholders, industry leads and lobby groups. Sometimes expert reviews by individuals or organisations can help shape effective policies. And sometimes the government needs to run a formal, open consultation; this provides transparency of emerging policy-thinking, and enables responses from anybody interested in that area.

The scrutiny and feedback provided by an open consultation is important for the healthy democratic process. Ensuring all of this feedback is appropriately reviewed and considered also places an enormous burden on government departments. They will try to steer responses through web forms for ease of analysis, but for accessibility reasons must accept them via any channel (answers on a postcard please…!). The analysis will be largely qualitative in nature, trawling through responses to gather evidence and insight, both to understand the public consensus, and to help build better policy.

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