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Buildings
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Text Mining and Natural Language Processing in the Built Environment
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Text Mining and Natural Language Processing in the Built Environment

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 496

Special Issue Editors

Dr. Maria Paula Mendes

E-Mail Website
Guest Editor
CERIS, Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portuga
Interests: sentiment classification; sustainable building environment; data mining
Dr. Jónatas Valença

E-Mail Website
Guest Editor
CERIS, Department of Civil Engineering, Architecture and Georesources, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, n.1, 1049-001 Lisbon, Portugal
Interests: inspection and diagnosis of built heritage; structural health monitoring; digital construction
Special Issues, Collections and Topics in MDPI journals
Dr. Ana Silva

E-Mail Website
Guest Editor
CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal
Interests: service life prediction, durability and life cycle of buildings and their components; maintenance modelling; statistical models
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The sustainability of the built environment can only be achieved through a set of goals, including greenhouse gas emission targets, decarbonizing the economy, promoting circularity, embracing digitalization, and enhancing biodiversity, all while respecting aesthetics and fostering inclusion. Ensuring that citizens are at the centre of this development is crucial for the success of all these measures. Furthermore, digitalization generates a substantial amount of information in electronically published formats, stored across various platforms, such as social media, emails, drawings, contracts, and news outlets, to name a few.

Text mining and natural language processing offer enhanced capabilities for managing and analysing text-based information in the construction sector and urban environment. Integrating these applications into sustainable development practices can further optimize decision-making processes, reveal patterns of behaviours, and support numerous sectors within the built environment. This Special Issue intends to provide an overview of the existing knowledge related with various aspects of Text Mining and Natural Language Processing in the Built Environment. Original research, theoretical and experimental, case studies, and comprehensive review papers are welcome. The relevant topics include, but are not limited to, the following subjects:

  1. The operation and maintenance of infrastructures;
  2. Risk assessment;
  3. Urban planning and development;
  4. Users’ preferences and perceptions;
  5. Safety management;
  6. Stakeholders management;
  7. Life cycle assessment. 

Dr. Maria Paula Mendes
Dr. Jónatas Valença
Dr. Ana Silva
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • operations and maintenance of infrastructures
  • risk assessment
  • urban planning and development
  • users’ preferences and perceptions
  • safety management
  • stakeholders management
  • life cycle assessment

Published Papers (1 paper)

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Research

19 pages, 2825 KiB  
Article
Seeing and Thinking about Urban Blue–Green Space: Monitoring Public Landscape Preferences Using Bimodal Data
by Chenglong Dao and Jun Qi
Buildings 2024, 14(5), 1426; https://doi.org/10.3390/buildings14051426 - 15 May 2024
Viewed by 228
Abstract
Urban blue–green spaces (UBGSs) are a significant avenue for addressing the worldwide mental health crisis. To effectively optimise landscape design and management for the promotion of health benefits from UBGS, it is crucial to objectively understand public preferences. This paper proposes a method [...] Read more.
Urban blue–green spaces (UBGSs) are a significant avenue for addressing the worldwide mental health crisis. To effectively optimise landscape design and management for the promotion of health benefits from UBGS, it is crucial to objectively understand public preferences. This paper proposes a method to evaluate public landscape preference from the perspective of seeing and thinking, takes the examples of seven parks around the Dianchi Lake in Kunming, China, and analyses the social media data by using natural language processing technology and image semantic segmentation technology. The conclusions are as follows: (1) The public exhibits significantly high positive sentiments towards various UBGSs, with over 93% of comments expressed positive sentiments. (2) Differences exist in the frequency and perception of landscape features between image and text modalities. Landscape elements related to stability are perceived more in images than in text, while dynamic and experiential elements are perceived more in text than in images. (3) In both modalities, the distinctive landscape features of parks are more frequently perceived and preferred by the public. In the end, the intrinsic links between landscape elements and public sentiment and preferences are discussed, and suggestions for design and management improvements are made to consolidate their health benefits to the public. Full article
(This article belongs to the Special Issue Text Mining and Natural Language Processing in the Built Environment)
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