@conference {263,
	title = {Digital Footprints of International Migration on Twitter},
	booktitle = {International Symposium on Intelligent Data Analysis},
	year = {2020},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Studying migration using traditional data has some limitations. To date, there have been several studies proposing innovative methodologies to measure migration stocks and flows from social big data. Nevertheless, a uniform definition of a migrant is difficult to find as it varies from one work to another depending on the purpose of the study and nature of the dataset used. In this work, a generic methodology is developed to identify migrants within the Twitter population. This describes a migrant as a person who has the current residence different from the nationality. The residence is defined as the location where a user spends most of his/her time in a certain year. The nationality is inferred from linguistic and social connections to a migrant{\textquoteright}s country of origin. This methodology is validated first with an internal gold standard dataset and second with two official statistics, and shows strong performance scores and correlation coefficients. Our method has the advantage that it can identify both immigrants and emigrants, regardless of the origin/destination countries. The new methodology can be used to study various aspects of migration, including opinions, integration, attachment, stocks and flows, motivations for migration, etc. Here, we exemplify how trending topics across and throughout different migrant communities can be observed.},
	author = {Jisu Kim and Alina Sirbu and Giannotti, Fosca and Gabrielli, Lorenzo}
}
@article {276,
	title = {Measuring objective and subjective well-being: dimensions and data sources},
	journal = {International Journal of Data Science and Analytics (JDSA)},
	year = {2020},
	abstract = {Well-being is an important value for people{\textquoteright}s lives, and it could be considered as an index of societal progress. Researchers have suggested two main approaches for the overall measurement of well-being, the objective and the subjective well-being. Both approaches, as well as their relevant dimensions, have been traditionally captured with surveys. During the last decades, new data sources have been suggested as an alternative or complement to traditional data. This paper aims to present the theoretical background of well-being, by distinguishing between objective and subjective approaches, their relevant dimensions, the new data sources used for their measurement and relevant studies. We also intend to shed light on still barely unexplored dimensions and data sources that could potentially contribute as a key for public policing and social development.},
	doi = {https://doi.org/10.1007/s41060-020-00224-2},
	author = {Vasiliki Voukelatou and Gabrielli, Lorenzo and Miliou, Ioanna and Cresci, Stefano and Sharma, Rajesh and Tesconi, Maurizio and Pappalardo, Luca}
}
