Crowdsourcing Pleasantness and Safety Perceptions: An Analysis through Multiple Rankings and Socio-Demographic Groups

References

• C. C. Aggarwal, Recommender Systems: The Textbook ([S.l.]: Springer, 2016).
   Google Scholar
• T. M. Al-Soliman, “The Impact of the Surrounding Environment on People’s Perception of Major Urban Environmental Attributes,” Architecture and Planning 2 (1990) 43–60.
   Google Scholar
• D. Appleyard, “Notes on Urban Perception and Knowledge,” Image and Environment 1 (1973) 109–114.
   Google Scholar
• F. Bos, R. Jaffe, “A Rejuvenated Approach to Urban Development and Inequality: Young People's Perceptions and Experiences in Rio De Janeiro,” Habitat International 48 (2015) 106–112.
   Web of Science ®Google Scholar
• D. Buil-Gil, R. Solymosi, A. Moretti, “Non-Parametric Bootstrap and Small Area Estimation to Mitigate Bias in Crowdsourced Data. Simulation Study and Application to Perceived Safety.” Big Data Meets Survey Science (2019) 1–32.
   Google Scholar
• D. Candeia et al., “Multiple Images of the City: Unveiling Group-Specific Urban Perceptions Through a Crowdsourcing Game,” paper presented at 28th ACM Conference on Hypertext and Social Media (2017).
   Google Scholar
• X. J. Cao, “How Does Neighborhood Design Affect Life Satisfaction? Evidence from Twin Cities,” Travel Behavior and Society 5 (2015) 68–76.
   Web of Science ®Google Scholar
• X. Chen et al., “Pairwise Ranking Aggregation in a Crowdsourced Setting,” paper presented at Sixth ACM International Conference on Web Search and Data Mining (2013).
   Google Scholar
• R. Damatta, Fé em Deus e Pé na Tábua: Ou Como e Por Que o Trânsito Enlouquece no Brasil ([S.l.]: Editora Rocco, 2012).
   Google Scholar
• K. Day, C. Stump, and D. Carreon, “Confrontation and Loss of Control: Masculinity and Men's Fear in Public Space,” Journal of Environmental Psychology 23: 3 (2003) 311–322.
   Web of Science ®Google Scholar
• A. Dubey et al., “Deep Learning the City: Quantifying Urban Perception at a Global Scale,” paper presented at European Conference on Computer Vision (2016).
   Google Scholar
• A. Elo, The Rating of Chessplayers, Past and Present ([S.l.]: Arco Pub., 1978).
   Google Scholar
• J. S. Evans-Cowley, and G. Akar, “Streetseen: Factors Influencing the Desirability of a Street for Bicycling,” Journal of the Transportation Research Board 2468 (2014) 19–27.
   Web of Science ®Google Scholar
• R. Ewing et al., Measuring Urban Design: Metrics for Livable Places (Washington, DC: Island Press, 2013)
   Google Scholar
• A. Gelman and J.: Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models ([S.l.]: Cambridge University Press, 2006).
   Google Scholar
• R. Goodspeed, X. Yan, “Crowdsourcing Street Beauty,” Big Data for Regional Science (Routledge, 2017) 75–93.
   Google Scholar
• C. Harvey et al., “Effects of Skeletal Streetscape Design on Perceived Safety,” Landscape and Urban Planning 142 (2015) 18–28.
   Web of Science ®Google Scholar
• Instituto Brasileiro de Geografia e Estatística, Sinopse do Censo Demográfico 2010 (Rio de Janeiro: IBGE, 2011).
   Google Scholar
• H. Izazola, C. Martinez, and C. Marquette, “Evironmental Perceptions, Social Class and Demographic Change in Mexico City: A Comparative Approach,” Environment and Urbanization 10 (1998) 107–118.
   Web of Science ®Google Scholar
• A. Jenkins et al., “Crowdsourcing a Collective Sense of Place,” PloS one 11: 4 (2016). https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152932
   Web of Science ®Google Scholar
• C. Jim and X. Shan, “Socioeconomic Effect on Perception of Urban Green Spaces in Guangzhou, China,Cties 31 (2013) 123–131.
   Web of Science ®Google Scholar
• M. J. Kelley, “The Emergent Urban Imaginaries of Geosocial Media,” GeoJournal 78: 1 (2013) 181–203.
   Google Scholar
• L. Liu, H. Wang, and C. Wu, “A Machine Learning Method for the Large-Scale Evaluation of Urban Visual Environment,” Computers, Environment and Urban Systems 65 (2016) 113–125.
   Web of Science ®Google Scholar
• K. Lynch, The Image of the City ([S.l.]: MIT Press, 1960).
   Google Scholar
• A. A. Marley, J. J. Louviere, “Some Probabilistic Models of Best, Worst, and Best–Worst Choices,” Journal of Mathematical Psychology 49 (2005) 464–480.
   Web of Science ®Google Scholar
• N. Naik et al., “Streetscore–Predicting the Perceived Safety of One Million Streetscapes,” paper presented at Computer Vision and Pattern Recognition Workshops (CVPRW) (2014).
   Google Scholar
• V. Ordonez and T. L. Berg, “Learning High-Level Judgments of Urban Perception,” paper presented at European Conference on Computer Vision (2014).
   Google Scholar
• B. Orme, “Maxdiff Analysis: Simple Counting, Individual-Level Logit, and Hb,” Sawtooth Software (2009). https://sawtoothsoftware.com/resources/technical-papers/maxdiff-analysis-simple-counting-individual-level-logit-and-hb
   Google Scholar
• F. Pedregosa et al., “Scikit-Learn: Machine Learning in Python,” Journal of Machine Learning Research 12 (2011) 2825–2830.
   Web of Science ®Google Scholar
• J. Peirce, “Divided Cities: Crime and Inequality in Urban Brazil,” Paterson Review 9 (2008) 85–98.
   Google Scholar
• L. Porzi et al., “Predicting and Understanding Urban Perception with Convolutional Neural Networks,” paper presented at 23rd ACM International Conference on Multimedia (2015).
   Google Scholar
• D. Quercia, N. K. O'Hare, and H. Cramer, “Aesthetic Capital: What Makes London Look Beautiful, Quiet, and Happy?,” paper presented at 17th ACM Conference on Computer Supported Cooperative Work & Social Computing (2014).
   Google Scholar
• A. M. Saks, G. Johns, “Perception, Attribution, and Judgment of Others,” in A. Saks, ed. 6, Organizational Behaviour: Understanding and Managing Life at Work (New York: Pearson College Div, 2005) 72–114.
   Google Scholar
• P. Salesses, K. Schechtner, and C. A. Hidalgo, “The Collaborative Image of the City: Mapping the Inequality of Urban Perception,” PloS One 8: 7 (2013). https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0068400
   PubMed Web of Science ®Google Scholar
• R. J. Sampson, S. W. Raudenbush, “Seeing Disorder: Neighborhood Stigma and the Social Construction of Broken Windows,” Social Psychology Quarterly 67: 4 (2004) 319–342.
   Web of Science ®Google Scholar
• H. W. Schroeder and L. M. Anderson, “Perception of Personal Safety in Urban Recreation Sites,” Journal of Leisure Research 16: 2 (1984).
   Web of Science ®Google Scholar
• R. Solymosi, K. J. Bowers, T. Fujiyama, “Crowdsourcing Subjective Perceptions of Neighbourhood Disorder: Interpreting Bias in Open Data,” The British Journal of Criminology (2017) 944–967.
   Web of Science ®Google Scholar
• W. C. Sullivan, F. E. Kuo, and S. F. Depooter. “The Fruit of Urban Nature: Vital Neighborhood Spaces, Environment and Behavior 36: 5 (2004) 678–700.
   Web of Science ®Google Scholar
• M. Traunmueller, P. Marshall, and L. Capra, “Crowdsourcing Safety Perceptions of People: Opportunities and Limitations,” paper presented at International Conference on Social Informatics (2015).
   Google Scholar
• R. S. Ulrich, “Human Responses to Vegetation and Landscapes,” Landscape and Urban Planning 13 (1986) 29–44.
   Web of Science ®Google Scholar
• E. A. Vasconcellos, Urban Transport Environment and Equity: The Case for Developing Countries (New York: Routledge, 2014)
   Google Scholar
• J. J.: Waiselfiz, Mapa da Violência 2013: Mortes Matadas por Armas de Fogo, report of gun deaths published by CEBELA (2013) http://mapadaviolencia.net.br/pdf2013/MapaViolencia2013_armas.pdf Acessed 09 09, 2020.
   Google Scholar
• G. Waitt, N. Gil, and L. Head, “Walking Practice and Suburban Nature-Talk,” Social and Cultural Geography 10: 1 (2009) 41–60.
   Web of Science ®Google Scholar
• R. Weber, J. Schnier, T. Jacobsen, “Aesthetics of Streetscapes: Influence of Fundamental Properties on Aesthetic Judgments of Urban Space,” Perceptual and Motor Skills 106 (2008) 128–146.
   PubMed Web of Science ®Google Scholar
• J. Q. Wilson, G. L. Kelling, “Broken Windows,” Atlantic Monthly, 249: 3 (1982) 309–319.
   Google Scholar
• S. Xiang, et al., “People-Centric Mobile Crowdsensing Platform for Urban Design,” paper presented at International Conference on Advanced Data Mining and Applications (2017).
   Google Scholar
• S. Yang, C. Pao, “Do We ‘See’ the Same Thing? An Experimental Look into the Black Box of Disorder Perception” Journal of Research in Crime and Delinquency 52 (2015) 534–566.
   Web of Science ®Google Scholar