PoiGraph Project

Welcome to the PoiGraph Project!

In this work, we show how social network analysis can be applied to lists of points of interest (POIs) in order to extract important information about the POIs and the relations between them. More precisely, we use public lists of POIs to build a social graph of POIs and then apply the Hyperlink-Induced Topic Search (HITS) algorithm and the Normalized Pointwise Mutual Information (NPMI) measure to estimate the user rating of each POI and the pairwise similarity between POIs, respectively. We evaluate our approach on POIs from the cities of Athens, Thessaloniki, and Rhodes. As a data source we use the corresponding user-speci ed lists of POIs of Foursquare, which are by default publicly accessible. Our results show that for each POI the authority score obtained with the HITS algorithm is strongly correlated with the actual rating of Foursquare. Moreover, preliminary evidence shows that the NPMI-based measure gives valuable information about the pairwise similarity between POIs.


  • @inproceedings{karagiannis2015social, title={Social network analysis of public lists of POIs}, author={Karagiannis, Ioannis and Arampatzis, Avi and Efraimidis, Pavlos S and Stamatelatos, Giorgos}, booktitle={Proceedings of the 19th Panhellenic Conference on Informatics}, pages={61--62}, year={2015}, organization={ACM}, doi={10.1145/2801948.2802031}, url={https://doi.org/10.1145/2801948.2802031} }