id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_ujjkmlhfpvf2xbwmlkrp43rayi	Albert Saiz	Crowdsourcing architectural beauty: Online photo frequency predicts building aesthetic ratings	2018	28	.pdf	application/pdf	3787	358	63	This section contains supplementary material for the paper "Crowdsourcing Architectural Beauty: Online Photo Frequency Predicts Building Aesthetic Ratings." about a building that are posted beyond the distances that we explore in the paper) will typically bias down the relationship between image uploads and the actual Table 2 of the main text are likely to underestimate their mean building beauty of the relationship between image uploads and building beauty. vertical axis, we group buildings by the number of photos uploaded in their vicinity, positive relationships between the number of uploaded photos and mean survey Table A1 shows the results of the regression that explains building beauty using Table A1: Estimates of the relationship between observed characteristics, building beauty and image uploads measures: OLS estimates Notes: The table shows the correlation between the observed architectural characteristics and building beauty. localized nature of the relationship between image uploads and building beauty, table A3 impact the covariance between assessed beauty and online photo frequencies	./cache/work_ujjkmlhfpvf2xbwmlkrp43rayi.pdf	./txt/work_ujjkmlhfpvf2xbwmlkrp43rayi.txt