Towards more effective online environmental information provision through tailored Natural Language Generation: Profiles of Scottish river user groups and an evaluative online experiment

Koen Arts,Christopher J.A Macleod,Antonio A.R Ioris,Xiwu Han,Somayajulu Sripada,João F Braga,Georgina Maffey,Nophadol Jekjantuk,Cheng Zeng,René Van Der Wal

doi:10.1016/j.scitotenv.2019.03.440

Abstract

As a result of societal transformations, political governance shifts, and advances in ICT, online information has become crucial in efforts by public authorities to make citizens better stewards of the environment. Yet, their environmental information provision may not always be attuned to end users' rationales, behaviours and appreciations. This study revolves around dynamic river level information provided by an environmental regulator – updated once a day or more, and collected by a sensor network of 333 gauging stations along 232 Scottish rivers. Employing an elaborate mixed methods approach with qualitative and quantitative elements, we examined if profiling of web page user groups and the subsequent employment of a specially designed Natural Language Generation (NLG) system could foster more effective online information provision. We identified profiles for the three main user groups: fishing, flood risk related, and paddling. The existence of well-distinguishable rationales and characteristics was in itself an argument for profiling; the same river level information was used in entirely different ways by the three groups. We subsequently constructed an advanced online experiment that implemented NLG based on live river level data. We found that textual information can be of much value in translating dynamic technical information into straightforward messages for the specific purposes of the user groups. We conclude that tailored NLG could be widely used in more effective online environmental information provision, and we provide five practical recommendations for public authorities and other information providers.

Highlights

Public authorities collecting data on the environment have an increased obligation to offer online information access to relevant audiences
Employing an elaborate mixed methods approach with qualitative and quantitative elements, we examined if profiling of web page user groups and the subsequent employment of a specially designed Natural Language Generation (NLG) system could foster more effective online information provision
Of all the experiment elements, the graph was the most looked at element (Fig. 6b). This may be surprising because it had no novelty factor, yet it was found in phase 1 that the graph was a trusted and highly appreciated feature of the Scottish Environment Protection Agency (SEPA) webpages for the fishing user group

Summary

Introduction

Public authorities collecting data on the environment have an increased obligation to offer online information access to relevant audiences This is in line with a global promotion to open public data (Mathur, 2009; Shadbolt et al, 2012) and with broader ‘political modernisation’ aspirations to replace ‘command and control’ regulation with ‘command and covenant’ stewardship (Arts and Leroy, 2006). The latter implies new societal roles for public authorities, with environmental information becoming a vehicle to generate citizen engagement with, and co-governance of, the natural environment (Bäckstrand, 2003; Fleischhauer et al, 2012). The importance of tailoring environmental information on such portals to meet the needs of users, is likewise increasingly recognised (see e.g. Christel et al, 2018 for the importance of differential provision of climate information to different sectors)

Methods

Results

Discussion

Conclusion