Youth unemployment rates are still in alerting levels for many countries, among which Italy. Direct consequences include poverty, social exclusion, and criminal behaviours, while negative impact on the future employability and wage cannot be obscured. In this study, we employ survey data together with social media data, and in particular likes on Facebook Pages, to analyse personality, moral values, but also cultural elements of the young unemployed population in Italy. Our findings show that there are small but significant differences in personality and moral values, with the unemployed males to be less agreeable while females more open to new experiences. At the same time, unemployed have a more collectivist point of view, valuing more in-group loyalty, authority, and purity foundations. Interestingly, topic modelling analysis did not reveal major differences in interests and cultural elements of the unemployed. Utilisation patterns emerged though; the employed seem to use Facebook to connect with local activities, while the unemployed use it mostly as for entertainment purposes and as a source of news, making them susceptible to mis/disinformation. We believe these findings can help policymakers get a deeper understanding of this population and initiatives that improve both the hard and the soft skills of this fragile population.

Urbinati, A., Kalimeri, K., Bonanomi, A., Rosina, A., Cattuto, C., Paolotti, D., Young Adult Unemployment Through the Lens of Social Media: Italy as a Case Study, Contributed paper, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (ita, 06-October 09-November 2020), Springer Science and Business Media Deutschland GmbH, Heidelberg 2020:<<LECTURE NOTES IN COMPUTER SCIENCE>>,12467 380-396. 10.1007/978-3-030-60975-7_28 [http://hdl.handle.net/10807/162731]

Young Adult Unemployment Through the Lens of Social Media: Italy as a Case Study

Bonanomi, Andrea;Rosina, Alessandro;
2020

Abstract

Youth unemployment rates are still in alerting levels for many countries, among which Italy. Direct consequences include poverty, social exclusion, and criminal behaviours, while negative impact on the future employability and wage cannot be obscured. In this study, we employ survey data together with social media data, and in particular likes on Facebook Pages, to analyse personality, moral values, but also cultural elements of the young unemployed population in Italy. Our findings show that there are small but significant differences in personality and moral values, with the unemployed males to be less agreeable while females more open to new experiences. At the same time, unemployed have a more collectivist point of view, valuing more in-group loyalty, authority, and purity foundations. Interestingly, topic modelling analysis did not reveal major differences in interests and cultural elements of the unemployed. Utilisation patterns emerged though; the employed seem to use Facebook to connect with local activities, while the unemployed use it mostly as for entertainment purposes and as a source of news, making them susceptible to mis/disinformation. We believe these findings can help policymakers get a deeper understanding of this population and initiatives that improve both the hard and the soft skills of this fragile population.
2020
Inglese
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12th International Conference on Social Informatics, SocInfo 2020
ita
Contributed paper
6-ott-2020
9-nov-2020
978-3-030-60974-0
Springer Science and Business Media Deutschland GmbH
Urbinati, A., Kalimeri, K., Bonanomi, A., Rosina, A., Cattuto, C., Paolotti, D., Young Adult Unemployment Through the Lens of Social Media: Italy as a Case Study, Contributed paper, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (ita, 06-October 09-November 2020), Springer Science and Business Media Deutschland GmbH, Heidelberg 2020:<<LECTURE NOTES IN COMPUTER SCIENCE>>,12467 380-396. 10.1007/978-3-030-60975-7_28 [http://hdl.handle.net/10807/162731]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/162731
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