In this paper, consideration is given to the use of new forms of social network data as a means to enrich our understanding of complex structures and activity patterns in urban areas. Specifically, a sample of Twitter messages (‘tweets’) in the city of Leeds is assembled from publicly available sources, and spatial and temporal patterns in these data are demonstrated, with special reference to the geodemographic profiles of service users. It is argued that classical space-time models of individual behaviour provide one possible framework for the interpretation of patterns, and the process of attempting to classify activities is begun with reference to the geographical distribution, timing and, importantly, the content of messages. Some init...
This paper explores the evolution and spatial organization of urban communities in a daily cycle of...
This paper presents the most recent developments in an on-going programme of work towards a realisti...
Location Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-te...
Increasingly large volumes of geo-located data from social messaging are available in the public dom...
Social media data are increasingly perceived as alternative sources to public attitude surveys becau...
AbstractSocial media data are increasingly perceived as alternative sources to public attitude surve...
The availability of vast amounts of location-based data from social media platforms such as Twitter ...
An in-depth descriptive approach to the dynamics of the urban population is fundamental as a first s...
Public streams of geo-located social media information have provided researchers with a rich source ...
Twitter, the most popular micro-blogging site, having over 500 million registered users as of 2012 a...
An in-depth descriptive approach to the dynamics of the urban population is fundamental as a first ...
This chapter presents the most recent developments in an on-going programme of work towards a realis...
Social networks attract lots of new users every day and ab- sorb from them information about events ...
Social networks attract lots of new users every day and ab- sorb from them information about events ...
An in-depth descriptive approach to the dynamics of the urban population is fundamental as a first ...
This paper explores the evolution and spatial organization of urban communities in a daily cycle of...
This paper presents the most recent developments in an on-going programme of work towards a realisti...
Location Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-te...
Increasingly large volumes of geo-located data from social messaging are available in the public dom...
Social media data are increasingly perceived as alternative sources to public attitude surveys becau...
AbstractSocial media data are increasingly perceived as alternative sources to public attitude surve...
The availability of vast amounts of location-based data from social media platforms such as Twitter ...
An in-depth descriptive approach to the dynamics of the urban population is fundamental as a first s...
Public streams of geo-located social media information have provided researchers with a rich source ...
Twitter, the most popular micro-blogging site, having over 500 million registered users as of 2012 a...
An in-depth descriptive approach to the dynamics of the urban population is fundamental as a first ...
This chapter presents the most recent developments in an on-going programme of work towards a realis...
Social networks attract lots of new users every day and ab- sorb from them information about events ...
Social networks attract lots of new users every day and ab- sorb from them information about events ...
An in-depth descriptive approach to the dynamics of the urban population is fundamental as a first ...
This paper explores the evolution and spatial organization of urban communities in a daily cycle of...
This paper presents the most recent developments in an on-going programme of work towards a realisti...
Location Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-te...