Spinsanti L., Berlingerio M., Pappalardo L.
Human Mobility Data Mining Network Science H.2.8 Database Applications. Data Mining
The Social Web is changing the way people create and use information. Every day millions of pieces of information are shared through the structure of many online social networks such as Facebook, Google+,Twitter, Foursquare, and so on. People have discovered a new way to exploit their sociality: from work to entertainment, from new participatory journalism to religion, from global to local government, from disaster management to market advertisement, from momently personal status update to milestone family events, the trend is to be social. Information or content are shared by users through the web by posting images or videos (e.g. on Flickr or YouTube), blogging or micro-blogging (Twitter),surveying and updating geographic information (OpenStreeMap), or playing geographic-based games (FourSquare). Considering the increase in mobile Internet access through smartphones and the number of (geo)social media platforms, we can expect the amount of information to continuously grow in the near future.This contribution discusses on the following questions: In which ways may location information relate to generated content on the web? How might this location be captured and represented? Where are possible sources for uncertainty (with respect to the location information)? Mobility and Geosocial networks: How the trajectories footprints in real word can be retrieved in the web, (and vice versa)?
Source: Mobility Data - Modeling, Management, and Understanding, edited by Chiara Renso, Stefano Spaccapietra, Esteban Zimányi, pp. 315–333, 2013
@inbook{oai:it.cnr:prodotti:278894, title = {Mobility and geo-social networks}, author = {Spinsanti L. and Berlingerio M. and Pappalardo L.}, booktitle = {Mobility Data - Modeling, Management, and Understanding, edited by Chiara Renso, Stefano Spaccapietra, Esteban Zimányi, pp. 315–333, 2013}, year = {2013} }