Using Natural Language Processing to Read Plans A Study of 78 Resilience Plans From the 100 Resilient Cities Network
Planners need to read plans to learn and adapt current practice. Planners may struggle to find time to read and study lengthy planning documents, especially in emerging areas such as climate change and urban resilience. Recently, natural language processing (NLP) has shown promise in processing big...
Gespeichert in:
| Veröffentlicht in: | Journal of the American Planning Association Jg. 89; H. 1; S. 107 - 119 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Routledge
02.01.2023
|
| Schlagworte: | |
| ISSN: | 0194-4363, 1939-0130 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Planners need to read plans to learn and adapt current practice. Planners may struggle to find time to read and study lengthy planning documents, especially in emerging areas such as climate change and urban resilience. Recently, natural language processing (NLP) has shown promise in processing big textual data. We asked whether planners could use NLP techniques to more efficiently extract useful and reliable information from planning documents. By analyzing 78 resilience plans from the 100 Resilient Cities Network, we found that results generated from topic modeling, which is an NLP technique, coincided to a large extent (80%) with those from the conventional content analysis approach. Topic modeling was generally effective and efficient in extracting the main information of plans, whereas the content analysis approach could find more in-depth details but at the expense of considerable time and effort. We further propose a transferrable model for cutting-edge planners to more efficiently read and study a large collection of plans using machine learning. Our methodology has limitations: Both topic modeling and content analysis can be subject to human bias and generate unreliable results; NLP text processing techniques may create inaccurate results due to their specific method limitations; and the transferable approach can be only applied to big textual data where there are enough sufficiently long documents.
NLP represents a valuable addition to the planner's toolbox. Topic modeling coupled with other NLP techniques can help planners to effectively discover key topics in plans, identify planning priorities and plans of specific emphasis, and find relevant policies. |
|---|---|
| AbstractList | Planners need to read plans to learn and adapt current practice. Planners may struggle to find time to read and study lengthy planning documents, especially in emerging areas such as climate change and urban resilience. Recently, natural language processing (NLP) has shown promise in processing big textual data. We asked whether planners could use NLP techniques to more efficiently extract useful and reliable information from planning documents. By analyzing 78 resilience plans from the 100 Resilient Cities Network, we found that results generated from topic modeling, which is an NLP technique, coincided to a large extent (80%) with those from the conventional content analysis approach. Topic modeling was generally effective and efficient in extracting the main information of plans, whereas the content analysis approach could find more in-depth details but at the expense of considerable time and effort. We further propose a transferrable model for cutting-edge planners to more efficiently read and study a large collection of plans using machine learning. Our methodology has limitations: Both topic modeling and content analysis can be subject to human bias and generate unreliable results; NLP text processing techniques may create inaccurate results due to their specific method limitations; and the transferable approach can be only applied to big textual data where there are enough sufficiently long documents.
NLP represents a valuable addition to the planner's toolbox. Topic modeling coupled with other NLP techniques can help planners to effectively discover key topics in plans, identify planning priorities and plans of specific emphasis, and find relevant policies. |
| Author | Fu, Xinyu Li, Chaosu Zhai, Wei |
| Author_xml | – sequence: 1 givenname: Xinyu orcidid: 0000-0002-3591-4158 surname: Fu fullname: Fu, Xinyu – sequence: 2 givenname: Chaosu orcidid: 0000-0002-1146-2361 surname: Li fullname: Li, Chaosu – sequence: 3 givenname: Wei orcidid: 0000-0003-4064-0427 surname: Zhai fullname: Zhai, Wei |
| BookMark | eNqFj8tKAzEUhoNUsFYfQZgXmDaXSTLBjVK8QdEidh3OZJISmSaSTJG-vR1bNy70LM5ZnP_74TtHoxCDReiK4CnBNZ5hoqqKCTalmNL9YrXg6gSNiWKqxIThERoPmXIInaHznN_xfhiXYzRbZR_WxTP02wRdsYCw3sLaFssUjc3fvz4WrxbaYtlByBfo1EGX7eXxTtDq_u5t_lguXh6e5reL0rCK9aWVqubMgSJYUcspKJBWtJJjxyUFKeq2ca6RvGFNVQtDq1YK0lBMsDBOtWyCrg-9JsWck3Xa-B56H0OfwHeaYD246x93Pbjro_ue5r_oj-Q3kHb_cjcHzgcX0wY-Y-pa3cOui8klCMZnzf6u-AJ2MXDv |
| CitedBy_id | crossref_primary_10_1177_08854122241229571 crossref_primary_10_1016_j_compenvurbsys_2024_102131 crossref_primary_10_1038_s41558_023_01890_3 crossref_primary_10_1177_0739456X251372082 crossref_primary_10_1016_j_ese_2025_100526 crossref_primary_10_1038_s44284_025_00261_7 crossref_primary_10_1177_08854122251360799 crossref_primary_10_1016_j_cities_2025_105898 crossref_primary_10_1007_s43762_022_00052_z crossref_primary_10_1016_j_cities_2025_106139 crossref_primary_10_1016_j_foar_2023_05_006 crossref_primary_10_1080_01944363_2024_2309259 crossref_primary_10_1007_s10758_025_09902_1 crossref_primary_10_2478_remav_2026_0001 crossref_primary_10_3390_urbansci8040197 crossref_primary_10_1080_01944363_2023_2271893 crossref_primary_10_1038_s40494_025_01715_w crossref_primary_10_1177_23998083251351743 crossref_primary_10_1177_23998083251369142 crossref_primary_10_1016_j_culher_2024_09_011 crossref_primary_10_1177_23998083241272097 |
| Cites_doi | 10.1177/0739456X14549752 10.1080/09640568.2016.1151771 10.1002/aris.1440370103 10.1080/01944369808975976 10.1080/01944363.2011.616995 10.1080/01944369708975926 10.1016/j.heliyon.2021.e06322 10.1002/asi.23596 10.1016/j.landurbplan.2015.11.011 10.1016/j.ijdrr.2020.101611 10.1007/s10584-019-02488-5 10.1371/journal.pone.0218590 10.1177/0739456X13513614 10.1177/0739456X02238446 10.2196/jmir.9702 10.1177/0739456X16647161 10.1177/147309520200100104 10.1016/j.cities.2021.103239 10.1080/01944363.2020.1831401 10.1038/s41893-019-0250-1 10.1080/17565529.2017.1301868 10.1177/0739456X18769134 10.1080/14649350802661741 10.1177/0049124118799372 10.1177/088541229601000302 10.1177/0885412208327014 10.1016/j.progress.2015.05.002 10.1177/1078087420938443 10.1080/01944363.2020.1766994 10.1080/01944363.2019.1652108 10.1016/j.cities.2016.05.011 10.1177/0739456X21995890 10.1080/08111146.2014.994741 10.1080/01944360008976081 10.1177/0739456X211048928 10.1080/01944360408976395 10.1038/nclimate3012 10.1080/01944363.2017.1404486 10.1080/02723638.2018.1446870 |
| ContentType | Journal Article |
| Copyright | 2022 American Planning Association, Chicago, IL. 2022 |
| Copyright_xml | – notice: 2022 American Planning Association, Chicago, IL. 2022 |
| DBID | AAYXX CITATION |
| DOI | 10.1080/01944363.2022.2038659 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Economics Architecture |
| EISSN | 1939-0130 |
| EndPage | 119 |
| ExternalDocumentID | 10_1080_01944363_2022_2038659 2038659 |
| Genre | Research Article |
| GroupedDBID | --Z -DZ -~X ..I .7I .QK 0BK 0R~ 29L 2DF 4.4 5VS 7WY 85S 8FL 8VB AAGDL AAGZJ AAHIA AAIKC AAMFJ AAMIU AAMNW AAPUL AATTQ AAZMC ABCCY ABDPE ABFIM ABISK ABJNI ABLIJ ABPEM ABQIJ ABRLO ABTAI ABUFD ABXUL ABXYU ABZLS ACGFO ACGFS ACHQT ACIWK ACTIO ACTOA ADAHI ADCVX ADKVQ ADMHG AECIN AEFOU AEGXH AEISY AEKEX AEMOZ AEOZL AEPSL AEYOC AEZRU AFRAH AFRVT AGDLA AGMYJ AGRBW AHDZW AHQJS AIAGR AIJEM AIYEW AJWEG AKBVH AKVCP ALMA_UNASSIGNED_HOLDINGS ALQZU AQTUD AVBZW AWYRJ BEJHT BLEHA BMOTO BOHLJ CCCUG CQ1 CS3 DGFLZ DKSSO DU5 EBS ESO E~B E~C FJW G-F GTTXZ H13 HF~ H~9 IPNFZ J.O K1G K60 K6~ KYCEM LJTGL M4Z NA5 NY- P2P QN7 QWB RIG RNANH ROSJB RSYQP S-F STATR TAE TASJS TBQAZ TDBHL TEG TFH TFL TFW TH9 TN5 TNTFI TRJHH TUROJ U5U UPT UT5 UT9 VAE WH7 YQT YZZ ZCA ZL0 ~01 ~S~ AAYXX CITATION |
| ID | FETCH-LOGICAL-c343t-e79853fa91092e52a9a7e6d750f572a768dbffb75b3b486c24d761b20106cf9d3 |
| IEDL.DBID | TFW |
| ISICitedReferencesCount | 28 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000813749500001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0194-4363 |
| IngestDate | Sat Nov 29 03:00:31 EST 2025 Tue Nov 18 21:51:36 EST 2025 Mon Oct 20 23:46:56 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c343t-e79853fa91092e52a9a7e6d750f572a768dbffb75b3b486c24d761b20106cf9d3 |
| ORCID | 0000-0002-3591-4158 0000-0003-4064-0427 0000-0002-1146-2361 |
| PageCount | 13 |
| ParticipantIDs | informaworld_taylorfrancis_310_1080_01944363_2022_2038659 crossref_citationtrail_10_1080_01944363_2022_2038659 crossref_primary_10_1080_01944363_2022_2038659 |
| PublicationCentury | 2000 |
| PublicationDate | 2023-01-02 |
| PublicationDateYYYYMMDD | 2023-01-02 |
| PublicationDate_xml | – month: 01 year: 2023 text: 2023-01-02 day: 02 |
| PublicationDecade | 2020 |
| PublicationTitle | Journal of the American Planning Association |
| PublicationYear | 2023 |
| Publisher | Routledge |
| Publisher_xml | – name: Routledge |
| References | CIT0010 CIT0032 CIT0031 CIT0034 CIT0011 CIT0033 CIT0014 Kelly E. D. (CIT0023) 2012 CIT0036 CIT0013 CIT0035 CIT0016 CIT0038 CIT0015 CIT0037 CIT0018 CIT0017 CIT0039 Nation P. (CIT0030) 2009; 9 CIT0019 CIT0041 CIT0040 CIT0043 CIT0020 CIT0042 CIT0001 CIT0045 CIT0022 CIT0044 Krippendorff K. (CIT0024) 2018 Fry E. (CIT0012) 1963 CIT0003 CIT0025 CIT0047 CIT0002 CIT0046 CIT0005 Hopkins L. D. (CIT0021) 2001 CIT0027 CIT0004 CIT0026 CIT0007 CIT0029 CIT0006 CIT0028 CIT0009 CIT0008 |
| References_xml | – ident: CIT0015 – ident: CIT0027 doi: 10.1177/0739456X14549752 – ident: CIT0013 doi: 10.1080/09640568.2016.1151771 – ident: CIT0009 doi: 10.1002/aris.1440370103 – ident: CIT0031 doi: 10.1080/01944369808975976 – ident: CIT0033 doi: 10.1080/01944363.2011.616995 – ident: CIT0001 doi: 10.1080/01944369708975926 – ident: CIT0008 doi: 10.1016/j.heliyon.2021.e06322 – ident: CIT0037 doi: 10.1002/asi.23596 – ident: CIT0028 doi: 10.1016/j.landurbplan.2015.11.011 – ident: CIT0046 doi: 10.1016/j.ijdrr.2020.101611 – ident: CIT0014 doi: 10.1007/s10584-019-02488-5 – ident: CIT0022 doi: 10.1371/journal.pone.0218590 – ident: CIT0035 doi: 10.1177/0739456X13513614 – ident: CIT0042 doi: 10.1177/0739456X02238446 – ident: CIT0016 doi: 10.2196/jmir.9702 – ident: CIT0007 doi: 10.1177/0739456X16647161 – ident: CIT0020 doi: 10.1177/147309520200100104 – ident: CIT0043 doi: 10.1016/j.cities.2021.103239 – volume: 9 start-page: 131 issue: 2 year: 2009 ident: CIT0030 publication-title: International Journal of English Studies – ident: CIT0039 – ident: CIT0018 doi: 10.1080/01944363.2020.1831401 – ident: CIT0010 doi: 10.1038/s41893-019-0250-1 – ident: CIT0003 doi: 10.1080/17565529.2017.1301868 – ident: CIT0036 doi: 10.1177/0739456X18769134 – ident: CIT0032 doi: 10.1080/14649350802661741 – ident: CIT0047 – ident: CIT0002 doi: 10.1177/0049124118799372 – ident: CIT0038 doi: 10.1177/088541229601000302 – ident: CIT0005 doi: 10.1177/0885412208327014 – ident: CIT0041 doi: 10.1016/j.progress.2015.05.002 – volume-title: Community planning: An introduction to the comprehensive plan year: 2012 ident: CIT0023 – volume-title: Teaching faster reading: A manual year: 1963 ident: CIT0012 – ident: CIT0019 doi: 10.1177/1078087420938443 – ident: CIT0011 doi: 10.1080/01944363.2020.1766994 – ident: CIT0029 doi: 10.1080/01944363.2019.1652108 – ident: CIT0034 doi: 10.1016/j.cities.2016.05.011 – volume-title: Content analysis: An introduction to its methodology year: 2018 ident: CIT0024 – ident: CIT0006 doi: 10.1177/0739456X21995890 – ident: CIT0040 doi: 10.1080/08111146.2014.994741 – ident: CIT0004 doi: 10.1080/01944360008976081 – volume-title: Urban development: The logic of making plans year: 2001 ident: CIT0021 – ident: CIT0045 doi: 10.1177/0739456X211048928 – ident: CIT0025 doi: 10.1080/01944360408976395 – ident: CIT0044 doi: 10.1038/nclimate3012 – ident: CIT0017 doi: 10.1080/01944363.2017.1404486 – ident: CIT0026 doi: 10.1080/02723638.2018.1446870 |
| SSID | ssj0000357 |
| Score | 2.480858 |
| Snippet | Planners need to read plans to learn and adapt current practice. Planners may struggle to find time to read and study lengthy planning documents, especially in... |
| SourceID | crossref informaworld |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 107 |
| SubjectTerms | machine learning natural language processing plan evaluation urban resilience |
| Subtitle | A Study of 78 Resilience Plans From the 100 Resilient Cities Network |
| Title | Using Natural Language Processing to Read Plans |
| URI | https://www.tandfonline.com/doi/abs/10.1080/01944363.2022.2038659 |
| Volume | 89 |
| WOSCitedRecordID | wos000813749500001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAWR databaseName: Taylor & Francis customDbUrl: eissn: 1939-0130 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000357 issn: 0194-4363 databaseCode: TFW dateStart: 19790101 isFulltext: true titleUrlDefault: https://www.tandfonline.com providerName: Taylor & Francis |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LSwMxEB5EBEXwURXrixy8rnWTbNIci1g8lOKham9LniBIK93V32-SzWp7UA96XmZZJtnMI_N9H8AlNoZpTa4z7KQvUAiXmRIMZ5pghbkj0kXU--OIj8f96VTcp2nCKo1VhhraNUQR8awOP7dUVTsR1_NZCaWEEV_d4YClCrKVAcLnM_uwxyfDp6-zmBQJME2zYNJieL57y0p0WuEuXYo6w91_-N492EkpJxo0e2Qf1uysA9uDpRuEDmy2AOXqAHpxjACNZaTkQKPU0UQJUxCe1XMUpu9RkDyqDuFheDu5ucuSroJfAUrqzHLhg7STPlMQ2BZYCsktMz53cAXH0hcgRjmneKGI8i7VmBrOchXuzZl2wpAjWJ_NZ_YYEOGF5tox7qSlhiqRE6e806UV_ZxY1QXa-rPUiXQ8aF-8lHnLTZqcUwbnlMk5Xbj6NHttWDd-MxDLi1XWsd3hGm2Skvxoe_IH21PYCvrzsSeDz2C9XrzZc9jQ7_VztbiIe_ED5s3XZw |
| linkProvider | Taylor & Francis |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3NS8MwFH_oFCaCH1Nxfvbgtc4mabIchzgm1p6m7laSNAFBNtmqf79Jm2p3UA96Lq-UX9K8j7zf-wFcoDynSuGrEBlhExTMRCg5RaHCSCJmsDAl6_0xYWnan0x4kwvj2ipdDm2qQRHlWe1-bleMrlviejYsIQRTbNM75MhUTreSr8JabH2ta-sbD5--TmMce8o0CZ1NzeL57jVL_mlpemnD7wy3_-OLd2DLR53BoNomu7Cipx3YHDQuETrQrjnKiz3olZ0EQSrKqRxB4ouagacVuGfFLHAN-IFTPVrsw8PwZnw9Cr20gl0EgotQM279tBE2WOBIx0hwwTTNbfhgYoaEzUFyaYxkscSS9KlCJGc0ku7qnCrDc3wArelsqg8hsJArpgxlRmiSE8kjbKRFXWjej7CWXSA1oJnyc8ed_MVLFtXjST04mQMn8-B04fLT7LUavPGbAW-uVlaUFQ9TyZNk-Efboz_YnkN7NL5PsuQ2vTuGDSdHX5Zo0Am0ivmbPoV19V48L-Zn5cb8AJaV24g |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3NS8MwFH_oFBXBj6k4P3vwWmeTNFmOQy2Ko-wwdbeSpAkIso2t-vebtKluB_Wg5_JKeUnzPvJ-vx_ABcpzqhS-CpERtkDBTISSUxQqjCRiBgtTot6feixNO8Mh7_tpwpkfq3Q1tKmIIsqz2v3ck9zUE3Ftm5UQgim21R1yWConW8mXYaUkx7JbepA8fx3GOPaIaRI6mxrE891rFsLTAnnpXNhJtv_hg3dgy-ecQbfaJLuwpEdN2OzOXSE0Yb1GKM_2oF3OEQSpKDk5gp5vaQYeVOCeFePAjd8HTvNotg-Pye3g-i70wgp2CQguQs24jdJG2FSBIx0jwQXTNLfJg4kZErYCyaUxksUSS9KhCpGc0Ui6i3OqDM_xATRG45E-hACzWDFlKDNCk5xIHmEjrdOF5p0Ia9kCUvszU5513IlfvGZRTU7qnZM552TeOS24_DSbVLQbvxnw-cXKirLfYSpxkgz_aHv0B9tzWOvfJFnvPn04hg2nRV_2Z9AJNIrpmz6FVfVevMymZ-W2_ADpLdos |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Using+Natural+Language+Processing+to+Read+Plans&rft.jtitle=Journal+of+the+American+Planning+Association&rft.au=Fu%2C+Xinyu&rft.au=Li%2C+Chaosu&rft.au=Zhai%2C+Wei&rft.date=2023-01-02&rft.pub=Routledge&rft.issn=0194-4363&rft.eissn=1939-0130&rft.volume=89&rft.issue=1&rft.spage=107&rft.epage=119&rft_id=info:doi/10.1080%2F01944363.2022.2038659&rft.externalDocID=2038659 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0194-4363&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0194-4363&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0194-4363&client=summon |