TY - JOUR
T1 - Towards more effective online environmental information provision through tailored Natural Language Generation
T2 - Profiles of Scottish river user groups and an evaluative online experiment
AU - Arts, Koen
AU - Macleod, Christopher J A
AU - Ioris, Antonio A R
AU - Han, Xiwu
AU - Sripada, Somayajulu
AU - Braga, Joao F
AU - Maffey, Georgina
AU - Jekjantuk, Nophadol
AU - Zeng, Cheng
AU - Van der Wal, Rene
N1 - The authors thank SEPA staff, particularly Bruce Eriksen, as well as all research informants and experiment participants for their time and effort. The research described here was supported by an award (EP/G066051/1) made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub at the University of Aberdeen
PY - 2019/7/10
Y1 - 2019/7/10
N2 - 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 provide five practical recommendations for public authorities and other information providers.
AB - 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 provide five practical recommendations for public authorities and other information providers.
KW - Environmental communication
KW - Environmental regulator
KW - Fishing
KW - NLG (Natural Language Generation)
KW - Public authorities
KW - River level
UR - http://www.scopus.com/inward/record.url?scp=85064151811&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/towards-more-effective-online-environmental-information-provision-through-tailored-natural-language
U2 - 10.1016/j.scitotenv.2019.03.440
DO - 10.1016/j.scitotenv.2019.03.440
M3 - Article
C2 - 30999105
VL - 673
SP - 643
EP - 655
JO - Science of the Total Environment
JF - Science of the Total Environment
SN - 0048-9697
ER -