LiveCities: Revealing the pulse of cities by location- based social networks venues and users analysis

WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web

Volumn , Issue , 2014, Pages 163-166

  Del Bimbo, Alberto ^a   Ferracani, Andrea ^a   Pezzatini, Daniele ^a   D'Amato, Federico ^a   Sereni, Martina ^a  

^a UNIVERSITY OF FLORENCE   (Italy)

Author keywords

Location based services; Recommendation systems; Smart cities; Venues classification

Indexed keywords

LOCATION; RECOMMENDER SYSTEMS; SEMANTICS; SOCIAL NETWORKING (ONLINE); TELECOMMUNICATION SERVICES; URBAN TRANSPORTATION; WORLD WIDE WEB;

ACTIVITY PATTERNS; CONTEXTUAL SEMANTICS; LOCATION-BASED SOCIAL NETWORKS; ONLINE QUESTIONNAIRE; PERSONAL RECOMMENDATIONS; SMART CITIES; SOCIAL DYNAMICS; WEB APPLICATION;

LOCATION BASED SERVICES;

EID: 84990934216     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2567948.2577035     Document Type: Conference Paper

References (7)

1. A.-E. Cano, A. Varga, and F. Ciravegna. Volatile classification of point of interests based on social activity streams. In In Proceedings of the 10th International Semantic Web Conference, Workshop on Social Data on the Web (SDoW), 2011.
2. Z. Cheng, J. Caverlee, K. Lee, and D. Z. Sui. Exploring Millions of Footprints in Location Sharing Services. In Proceedings of the Fifth International Conference on Weblogs and Social Media, Menlo Park, CA, USA, July 2011. AAAI.
3. J. Cranshaw, R. Schwartz, J. I. Hong, and N. M. Sadeh. The livehoods project: Utilizing social media to understand the dynamics of a city. In Proceedings of the Sixth International AAAI Conference on Weblogs an Social Media (ICWSM 2012), 2012.
4. L. Hong, A. Ahmed, S. Gurumurthy, A. J. Smola, and K. Tsioutsiouliklis. Discovering geographical topics in the twitter stream. In Proceedings of the 21st International Conference on World Wide Web, WWW '12, pages 769-778, New York, NY, USA, 2012. ACM.
5. A. Noulas, S. Scellato, C. Mascolo, and M. Pontil. Exploiting semantic annotations for clustering geographic areas and users in location-based social networks. In The Social Mobile Web, 2011.
6. Y. Qu and J. Zhang. Trade area analysis using user generated mobile location data. In Proceedings of the 22Nd International Conference on World Wide Web, WWW '13, pages 1053-1064, Republic and Canton of Geneva, Switzerland, 2013. International World Wide Web Conferences Steering Committee.
7. I. H. Witten and D. Milne. An effective, low-cost measure of semantic relatedness obtained from wikipedia links. In Proceeding of AAAI Workshop on Wikipedia and Artificial Intelligence: An Evolving Synergy, AAAI Press, Chicago, USA, pages 25-30, 2008.