Deciphering Public Voices in the Digital Era

Fu, Xinyu; Sanchez, Thomas W.; Li, Chaosu; Reu Junqueira, Juliana

doi:10.1080/01944363.2024.2309259

Journal of the American Planning Association

2024

DOI: 10.1080/01944363.2024.2309259

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Deciphering Public Voices in the Digital Era

Xinyu Fu,

Thomas W. Sanchez,

Chaosu Li

et al.

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2024

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Cited by 3 publications

References 42 publications

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A hybrid deep learning method for identifying topics in large-scale urban text data: Benefits and trade-offs

Lore,

Harten,

Boeing

2024

Computers, Environment and Urban Systems

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A hybrid deep learning method for identifying topics in large-scale urban text data: Benefits and trade-offs

Lore,

Harten,

Boeing

2024

Computers, Environment and Urban Systems

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Insights on the obstacles, challenges, and complexities of engaging youth in urban planning in Jordan: assessment and recommendations

Zeadat,

Haddad

2024

ARCH

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PurposeThis paper comprehensively investigates the lack of youth involvement in the intricate tapestry of urban policymaking in the Jordanian context. It attempts to present and illustrate the obstacles, challenges, hindrances and complexities facing engaging youth in urban planning in Jordan. Participants aged 18–24 were the primary focus of the investigation, as Jordan's population is predominantly youthful, with approximately 70% of the population under the age of 30.Design/methodology/approachThe research methodology adopted in this study is a mixed-methods approach, which integrates both qualitative and quantitative data collection and analytical techniques to provide a comprehensive and nuanced understanding of the research problem.FindingsYouth involvement in Jordan's urban policymaking is limited and inconsistent. Most notably, the prevalence of adultism emerges as the predominant and most substantive impediment, exerting a considerable influence on constraining the agency of young Jordanians in shaping urban policy.Research limitations/implicationsDetailed examples can be developed to offer discerning elucidations relevant to each frame of reference.Practical implicationsA total of 12 discernible barriers emerged from a systematic deductive thematic analysis of primary data.Originality/valueThis comprehensive inquiry highlights the pervasive gaps in support for youth participation in urban policymaking within the administrative framework and across Jordanian society. Subsequent quantitative analysis was employed to strengthen the external validity of the research findings, thereby enhancing the generalizability of the qualitative insights. By employing Jordan as a case study, this paper significantly contributes to the expanding corpus of scholarly work on planning processes and practices within the Global South and the Arab world.

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Text mining public feedback on urban densification plan change in Hamilton, New Zealand

Fu,

Brinkley,

Sanchez

et al. 2024

Environment and Planning B: Urban Analytics and City Science

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Cities worldwide are commonly aspiring to transition from inefficient urban sprawl patterns to more compact and sustainable urban forms. However, urban densification efforts often face significant public resistance or skepticism, hindering at-scale implementation. There is a scarcity of empirical studies identifying the rationale and mechanisms underpinning public opposition to urban density. This study aims to bridge this gap by leveraging novel natural language processing techniques (NLP), combined with mixed-methods analysis of a unique, highly detailed public dataset on urban intensification in Hamilton. This research stands out by proposing a transferable model for rapidly generating insights from large public feedback datasets, and also unveils the polarized and complex, self-interest-driven mechanisms, including NIMBYism (Not In My Back Yard), behind public support or opposition to urban densification. NLP techniques, such as sentiment analysis, topic modeling, and ChatGPT, can be used to offer rapid insights into a large, unstructured public feedback dataset. When combined with submitters’ individual interest representation and identifies, these AI-generated summaries can offer important insights into the hidden rationales behind public opinions, and, more importantly, be used to design tailored public engagement activities to obtain community buy-in.

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Deciphering Public Voices in the Digital Era

Cited by 3 publications

References 42 publications

A hybrid deep learning method for identifying topics in large-scale urban text data: Benefits and trade-offs

A hybrid deep learning method for identifying topics in large-scale urban text data: Benefits and trade-offs

Insights on the obstacles, challenges, and complexities of engaging youth in urban planning in Jordan: assessment and recommendations

Text mining public feedback on urban densification plan change in Hamilton, New Zealand

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