about
sameAs
Daniele Quercia: Happy mapsChatty maps: constructing sound maps of urban areas from social media data.Like Partying? Your Face Says It All. Predicting the Ambiance of Places with Profile PicturesWorld wide spatial capital.Diversity of indoor activities and economic development of neighborhoods.Recommending Social Events from Mobile Phone Location DataMapping and Visualizing Deep-Learning Urban BeautificationThe personality of popular facebook usersPartisan sharingRecommending investors for crowdfunding projectsSharing political news: the balancing act of intimacy and socialization in selective exposureWhy individuals seek diverse opinions (or why they don't)Ads and the cityThe Hidden Image of the City: Sensing Community Well-Being from Urban MobilityLoosing "friends" on FacebookOur Twitter Profiles, Our Selves: Predicting Personality with TwitterRecsys'11 workshop outline PeMA 2011SpotME If You Can: Randomized Responses for Location Obfuscation on Mobile PhonesMobiRate4th Workshop on Context-Awareness in Retrieval and RecommendationReport on the 4th Workshop on Context-awareness in Retrieval and Recommendation (CaRR 2014)Smelly Maps: The Digital Life of Urban SmellscapesHearts and Politics: Metrics for Tracking Biorhythm Changes during Brexit and TrumpLarge-scale and high-resolution analysis of food purchases and health outcomes
P50
Q23464914-EC5E2F62-A667-4D34-A8D1-61E0549EF204Q28601213-9A21D1B6-223A-409B-A9D2-D118965ABEBAQ48326277-53F77C19-8FF7-4858-8ACF-590B1F72EBF4Q50114226-7B2D6486-AEF9-454F-8492-8292319423C0Q55440862-856E4C3F-5002-423A-9DF5-DC1D56494DBDQ56094394-7AA2D3DC-23C8-4B7A-A13C-72A1293CA07CQ57122716-156770E1-4EF6-4554-B3BB-C2217E10991DQ57225301-E27B5B02-5AB3-4665-AA04-7F49D3D9C2CAQ57352508-28536C99-742D-44B2-91B3-0A51367A01FDQ57352523-2FD1DFAA-0984-4831-92D3-8C5ADC09FFCCQ57352530-6ADC6B62-FD66-451F-BE45-36ABA4B51F4AQ57352733-30BEA957-1F40-4465-A3C7-1F9F7E527064Q57352739-523A5B67-95BD-4EC7-826E-B54620A64DC3Q57352892-1E2094C7-59CF-452A-B1E5-A9CD2AB783BEQ57352902-6EA67929-1085-48F3-987F-2384C2622735Q57352974-7057C57D-2A45-41DE-BDC8-1071449D70F0Q57352982-3D34744F-3645-43BA-8F13-FB1E741A5BCBQ57352995-7DFCB53F-4D7E-4D8D-B967-B90F474CA99DQ63101685-E1D48970-F7A0-4CDB-988D-C0608C943C9FQ64060367-7A6DE7F4-11FB-40BC-AB43-7C1B6CB28D63Q64060370-9E50726D-2EC2-432E-A27D-722082A17480Q64414890-4407ede8-4012-3a6a-5d4f-57327b7d9737Q64414900-a6b6c789-4787-f655-490d-8b6e59955914Q64415202-d5826d89-4c06-6320-cf26-3717bc00ef91
P50
description
onderzoeker
@nl
researcher; urban informatics; King's College London, Nokia Bell Labs, Yahoo! Labs
@en
name
Daniele Quercia
@af
Daniele Quercia
@an
Daniele Quercia
@ast
Daniele Quercia
@bar
Daniele Quercia
@br
Daniele Quercia
@ca
Daniele Quercia
@co
Daniele Quercia
@cs
Daniele Quercia
@cy
Daniele Quercia
@da
type
label
Daniele Quercia
@af
Daniele Quercia
@an
Daniele Quercia
@ast
Daniele Quercia
@bar
Daniele Quercia
@br
Daniele Quercia
@ca
Daniele Quercia
@co
Daniele Quercia
@cs
Daniele Quercia
@cy
Daniele Quercia
@da
prefLabel
Daniele Quercia
@af
Daniele Quercia
@an
Daniele Quercia
@ast
Daniele Quercia
@bar
Daniele Quercia
@br
Daniele Quercia
@ca
Daniele Quercia
@co
Daniele Quercia
@cs
Daniele Quercia
@cy
Daniele Quercia
@da
P106
P1416
P1960
nPyDLd0AAAAJ
P2002
danielequercia
P21
P2456
P2611
daniele_quercia
P31
P496
0000-0001-9461-5804