File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Twitter sentiment in New York City parks as measure of well-being

TitleTwitter sentiment in New York City parks as measure of well-being
Authors
Issue Date2019
Citation
Landscape and Urban Planning, 2019, v. 189, p. 235-246 How to Cite?
AbstractWhile there is an extensive literature regarding the benefits of natural environments within urban settings, there is relatively little statistical research on the correlation of well-being with urban green space. This research uses social media to develop a methodology for understanding the varying levels of feelings in urban green space. Using a geolocated Twitter database, this research correlates quantified sentiment levels inside parks in New York City. It addresses the following: are people more positive when they are in parks as compared to when they are in other places? Specifically, among Twitter users in New York City do people who visit parks have more positive Twitter-sentiment expression compared to their sentiment in other places? Our results show that sentiment expressed in tweets varies between areas inside and outside of parks. We find that in Manhattan in-park tweets express less positive sentiment as compared to tweets outside of parks, but park visitors in the other boroughs of New York City generate more positive in-park tweets as compared to those outside of parks. We discuss the use of tweets as an indicator of the public expressed sentiment and derive suggestions for further research.
Persistent Identifierhttp://hdl.handle.net/10722/303608
ISSN
2021 Impact Factor: 8.119
2020 SCImago Journal Rankings: 1.938
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorPlunz, Richard A.-
dc.contributor.authorZhou, Yijia-
dc.contributor.authorCarrasco Vintimilla, Maria Isabel-
dc.contributor.authorMckeown, Kathleen-
dc.contributor.authorYu, Tao-
dc.contributor.authorUguccioni, Laura-
dc.contributor.authorSutto, Maria Paola-
dc.date.accessioned2021-09-15T08:25:39Z-
dc.date.available2021-09-15T08:25:39Z-
dc.date.issued2019-
dc.identifier.citationLandscape and Urban Planning, 2019, v. 189, p. 235-246-
dc.identifier.issn0169-2046-
dc.identifier.urihttp://hdl.handle.net/10722/303608-
dc.description.abstractWhile there is an extensive literature regarding the benefits of natural environments within urban settings, there is relatively little statistical research on the correlation of well-being with urban green space. This research uses social media to develop a methodology for understanding the varying levels of feelings in urban green space. Using a geolocated Twitter database, this research correlates quantified sentiment levels inside parks in New York City. It addresses the following: are people more positive when they are in parks as compared to when they are in other places? Specifically, among Twitter users in New York City do people who visit parks have more positive Twitter-sentiment expression compared to their sentiment in other places? Our results show that sentiment expressed in tweets varies between areas inside and outside of parks. We find that in Manhattan in-park tweets express less positive sentiment as compared to tweets outside of parks, but park visitors in the other boroughs of New York City generate more positive in-park tweets as compared to those outside of parks. We discuss the use of tweets as an indicator of the public expressed sentiment and derive suggestions for further research.-
dc.languageeng-
dc.relation.ispartofLandscape and Urban Planning-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleTwitter sentiment in New York City parks as measure of well-being-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1016/j.landurbplan.2019.04.024-
dc.identifier.scopuseid_2-s2.0-85065539138-
dc.identifier.volume189-
dc.identifier.spage235-
dc.identifier.epage246-
dc.identifier.isiWOS:000474330500022-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats