DOI

Social media has emerged as one of the data backbones of urban analytics systems. Thanks to geo-located microposts (text-, image-, and video-based) created and shared through portals such as Twitter and Instagram, scientists and practitioners can capitalise on the availability of real-time and semantically rich data sources to perform studies related to cities and the people inhabiting them. Urban analytics systems usually consider the micro posts originating from within a city’s boundary uniformly, without consideration for the demographic (e.g. gender, age), geographic, technological or contextual (e.g. role in the city) differences among a platform’s users. It is well-known though, that the usage and adoption of social media profoundly differ across user segments, cities, as well as countries. We thus advocate for a better understanding of the intrinsic diversity of social media users and contents. This paper presents an observational study of the geo-located activities of users across two social media platforms, performed over a period of three weeks in four European cities. We show how demographic, geographical, technological and contextual properties of social media (and their users) can provide very different reflections and interpretations of the reality of an urban environment.

Original languageEnglish
Title of host publicationWeb Engineering - 16th International Conference, ICWE 2016
Subtitle of host publicationProceedings
EditorsAlessandro Bozzon, Philippe Cudre-Maroux, Cesare Pautasso
Place of PublicationCham
PublisherSpringer International Publishing
Pages335-353
Number of pages19
ISBN (Electronic)978-3-319-38791-8
ISBN (Print)978-3-319-38790-1
DOIs
StatePublished - 2016
Event16th International Conference on Web Engineering, ICWE 2016 - Lugano, Switzerland

Publication series

NameLecture Notes in Computer Science
Volume9671
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Web Engineering, ICWE 2016
CountrySwitzerland
CityLugano
Period6/06/169/06/16

    Research areas

  • Social sensing, Urban analytics, User analysis

ID: 10683225