Skip to main content

2021 | OriginalPaper | Buchkapitel

Divorce in Italy: A Textual Analysis of Cassation Judgment

verfasst von : Rosanna Cataldo, Maria Gabriella Grassia, Marina Marino, Rocco Mazza, Vincenzo Pastena, Emma Zavarrone

Erschienen in: Data Science and Social Research II

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The dissolution of marriage is a complex social phenomenon that needs new topics of investigation, especially concerning the role of legal institutions in the conflict between partners. The research aims to identify the main issues that emerge in the institutional dimension of the phenomenon, identifying evolution and complexity of this within the sentences of the Italian Court of Cassation. Through judgments’ analysis we can trace the variety of the phenomenon and identify interpretations of law in line with the evolution of contemporary institutions. The sentences are inserted in a demographic framework and are subsequently explored with topic probabilistic model (Latent Dirichlet Allocation), aimed to trace latent topic. In conclusion, the topics extracted refer to three main-dimensions, one to the procedural phases, another concerns the difficulty of leaving the separation phase and ending up in divorce, and finally the debate on the social-economic measures of divorce maintenance.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Berry, M. W., & Kogan, J. (2010). Text mining: applications and theory. Wiley. Berry, M. W., & Kogan, J. (2010). Text mining: applications and theory. Wiley.
Zurück zum Zitat Blei, D. M., & Lafferty, J. D. (2007). A correlated topic model of science. The Annals of Applied Statistics, 1(1), 17–35. Blei, D. M., & Lafferty, J. D. (2007). A correlated topic model of science. The Annals of Applied Statistics, 1(1), 17–35.
Zurück zum Zitat Blei, D. M., Lafferty, J. D. (2009). Topic models. In Text mining (pp. 101–124). Chapman and Hall/CRC. Blei, D. M., Lafferty, J. D. (2009). Topic models. In Text mining (pp. 101–124). Chapman and Hall/CRC.
Zurück zum Zitat Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.
Zurück zum Zitat Bolasco, S., & De Mauro, T. (2013). L’analisi automatica dei testi: fare ricerca con il text mining, Carocci Editore. Bolasco, S., & De Mauro, T. (2013). L’analisi automatica dei testi: fare ricerca con il text mining, Carocci Editore.
Zurück zum Zitat Buntine, W. (2009). Estimating likelihoods for topic models. In: Asian Conference on Machine Learning (pp. 51-64). Berlin, Heidelberg: Springer. Buntine, W. (2009). Estimating likelihoods for topic models. In: Asian Conference on Machine Learning (pp. 51-64). Berlin, Heidelberg: Springer.
Zurück zum Zitat Chang, J., & Blei, D. (2009). Relational topic models for document networks. In Artificial Intelligence and Statistics (pp. 81–88). Chang, J., & Blei, D. (2009). Relational topic models for document networks. In Artificial Intelligence and Statistics (pp. 81–88).
Zurück zum Zitat Faust, K. (1997). Centrality in affiliation networks. Social Networks, 19(2), 157–191.CrossRef Faust, K. (1997). Centrality in affiliation networks. Social Networks, 19(2), 157–191.CrossRef
Zurück zum Zitat Griffiths, T. L., & Steyvers, M. (2002). A probabilistic approach to semantic representation. In Proceedings of the annual meeting of the cognitive science society, vol. 24, no. 24. Griffiths, T. L., & Steyvers, M. (2002). A probabilistic approach to semantic representation. In Proceedings of the annual meeting of the cognitive science society, vol. 24, no. 24.
Zurück zum Zitat Griffiths, T. L., & Steyvers, M. (2003). Prediction and semantic association. In Advances in Neural Information Processing Systems (pp. 11–18). Griffiths, T. L., & Steyvers, M. (2003). Prediction and semantic association. In Advances in Neural Information Processing Systems (pp. 11–18).
Zurück zum Zitat Griffiths, T. L., Steyvers, M., Blei, D. M., & Tenenbaum, J. B. (2005). Integrating topics and syntax. In Advances in Neural Information Processing Systems (pp. 537–544). Griffiths, T. L., Steyvers, M., Blei, D. M., & Tenenbaum, J. B. (2005). Integrating topics and syntax. In Advances in Neural Information Processing Systems (pp. 537–544).
Zurück zum Zitat Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101, 5228–5235.CrossRef Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101, 5228–5235.CrossRef
Zurück zum Zitat Heinrich, G. (2005). Parameter estimation for text analysis. Technical report. Heinrich, G. (2005). Parameter estimation for text analysis. Technical report.
Zurück zum Zitat Hofmann, T. (1999). Probabilistic latent semantic analysis. In Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (pp. 289–296). Morgan Kaufmann Publishers Inc. Hofmann, T. (1999). Probabilistic latent semantic analysis. In Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (pp. 289–296). Morgan Kaufmann Publishers Inc.
Zurück zum Zitat Hofmann, T. (2001). Unsupervised learning by probabilistic latent semantic analysis. Machine Learning, 42(1–2), 177–196.CrossRef Hofmann, T. (2001). Unsupervised learning by probabilistic latent semantic analysis. Machine Learning, 42(1–2), 177–196.CrossRef
Zurück zum Zitat ISTAT (2016b). Le trasformazioni demografiche e sociali: una lettura per generazione. ISTAT (2016b). Le trasformazioni demografiche e sociali: una lettura per generazione.
Zurück zum Zitat ISTAT (2018). Annuario statistico italiano. ISTAT (2018). Annuario statistico italiano.
Zurück zum Zitat Lebart, L., Morineau, A., & Piron, M. (1995). Statistique exploratoire multidimensionnelle (Vol. 3). Paris: Dunod.MATH Lebart, L., Morineau, A., & Piron, M. (1995). Statistique exploratoire multidimensionnelle (Vol. 3). Paris: Dunod.MATH
Zurück zum Zitat Neapolitan, R. E. (2003). Learning Bayesian networks, vol. 58, no. 4 (pp. 1064–1082). Prentice-Hall. Neapolitan, R. E. (2003). Learning Bayesian networks, vol. 58, no. 4 (pp. 1064–1082). Prentice-Hall.
Zurück zum Zitat Ponweiser, M. (2012). Latent Dirichlet allocation in R. Ponweiser, M. (2012). Latent Dirichlet allocation in R.
Zurück zum Zitat Steyvers M., & Griffiths T. (2007). Probabilistic topic models. In: T. Landauer, D. Mcnamara, S. Dennis & W. Kintsch (Eds.), Latent semantic analysis: a road to meaning (p. 427). Lawrence Erlbaum. Steyvers M., & Griffiths T. (2007). Probabilistic topic models. In: T. Landauer, D. Mcnamara, S. Dennis & W. Kintsch (Eds.), Latent semantic analysis: a road to meaning (p. 427). Lawrence Erlbaum.
Zurück zum Zitat Wallach, H. M., Murray, I., Salakhutdinov, R., & Mimno, D. (2009). Evaluation methods for topic models. In Proceedings of the 26th Annual International Conference on Machine Learning (pp. 1105–1112). ACM. Wallach, H. M., Murray, I., Salakhutdinov, R., & Mimno, D. (2009). Evaluation methods for topic models. In Proceedings of the 26th Annual International Conference on Machine Learning (pp. 1105–1112). ACM.
Metadaten
Titel
Divorce in Italy: A Textual Analysis of Cassation Judgment
verfasst von
Rosanna Cataldo
Maria Gabriella Grassia
Marina Marino
Rocco Mazza
Vincenzo Pastena
Emma Zavarrone
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-51222-4_21

Premium Partner