Milli L., Monreale A., Rossetti G., Pedreschi D., Giannotti F., Sebastiani F.
Quantification Network Science Community Discovery
In many real-world applications there is a need to monitor the distribution of a population across different classes, and to track changes in this distribution over time. As an example, an important task is to monitor the percentage of unemployed adults in a given region. When the membership of an individual in a class cannot be established deterministically, a typical solution is the classification task. However, in the above applications the final goal is not determining which class the individuals belong to, but estimating the prevalence of each class in the unlabeled data. This task is called quantification. Most of the work in the literature addressed the quantification problem considering data presented in conventional attribute format. Since the ever-growing availability of web and social media we have a flourish of network data representing a new important source of information and by using quantification network techniques we could quantify collective behavior, i.e., the number of users that are involved in certain type of activities, preferences, or behaviors. In this paper we exploit the homophily effect observed in many social networks in order to construct a quantifier for networked data. Our experiments show the effectiveness of the proposed approaches and the comparison with the existing state-of-the-art quantification methods shows that they are more accurate.
Source: IEEE International Conference on Data Science and Advanced Analytics, Paris, France, 19-21/10/2015
@inproceedings{oai:it.cnr:prodotti:345112, title = {Quantification in social networks}, author = {Milli L. and Monreale A. and Rossetti G. and Pedreschi D. and Giannotti F. and Sebastiani F.}, doi = {10.1109/dsaa.2015.7344845}, booktitle = {IEEE International Conference on Data Science and Advanced Analytics, Paris, France, 19-21/10/2015}, year = {2015} }
Giannotti, Fosca
0000-0003-3099-3835
Milli, Letizia
0000-0001-5283-0477
Monreale, Anna
0000-0001-8541-0284
Pedreschi, Dino
0000-0003-4801-3225
Rossetti, Giulio
0000-0003-3373-1240
Sebastiani, Fabrizio
0000-0003-4221-6427
Knowledge Discovery and Data Mining (2002-ongoing)
Networked Multimedia Information System (2002-2020)
CIMPLEX
Bringing CItizens, Models and Data together in Participatory, Interactive SociaL EXploratories