Giovanni Di Franco
Biographic Data
| ID | 4165605 |
|---|---|
| NAME | Giovanni Di Franco |
| GIVEN NAMES | Giovanni |
| FAMILY NAME | Di Franco |
| SIGNATURE | DI FRANCO G |
| AFFILIATIONS | Sapienza University of Rome |
| ORCID | 0000-0002-3159-0782 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
The return of non-probability sample
For the past 80 years survey researchers have used a probability sampling framework. Probability samples have a well-defined set of quality criteria that have been organized around the concept of Total Survey Error (TSE). Non-probability samples do not fit within this framework very well and some possible alternatives to TSE are explored. In recent years, electoral polls have undergone changes as a result of the dispersion of public opinion due m…
La trasparenza e l’affidabilità dei sondaggi elettorali in Italia al tempo di internet e dei social media
The article presents the results of a research on electoral polls disseminated by the mass media in Italy and published on the institutional website www.sondaggipoliticoelettorali.it. All the electoral polls published on the institutional website from 1 January 2017 to 9 September 2022 were analyzed. In the period considered, 1.537 polls were published. The article examines their sample size, their response rates in relation to the different inte…
Machine learning, artificial neural networks and social research
Machine learning (ML), and particularly algorithms based on artificial neural networks (ANNs), constitute a field of research lying at the intersection of different disciplines such as mathematics, statistics, computer science and neuroscience. This approach is characterized by the use of algorithms to extract knowledge from large and heterogeneous data sets. In addition to offering a brief introduction to ANN algorithms-based ML, in this paper w…
No prominent works on this page.
Machine learning, artificial neural networks and social research
Machine learning (ML), and particularly algorithms based on artificial neural networks (ANNs), constitute a field of research lying at the intersection of different disciplines such as mathematics, statistics, computer science and neuroscience. This approach is characterized by the use of algorithms to extract knowledge from large and heterogeneous data sets. In addition to offering a brief introduction to ANN algorithms-based ML, in this paper w…
La trasparenza e l’affidabilità dei sondaggi elettorali in Italia al tempo di internet e dei social media
The article presents the results of a research on electoral polls disseminated by the mass media in Italy and published on the institutional website www.sondaggipoliticoelettorali.it. All the electoral polls published on the institutional website from 1 January 2017 to 9 September 2022 were analyzed. In the period considered, 1.537 polls were published. The article examines their sample size, their response rates in relation to the different inte…
The return of non-probability sample
For the past 80 years survey researchers have used a probability sampling framework. Probability samples have a well-defined set of quality criteria that have been organized around the concept of Total Survey Error (TSE). Non-probability samples do not fit within this framework very well and some possible alternatives to TSE are explored. In recent years, electoral polls have undergone changes as a result of the dispersion of public opinion due m…
Computer Science (3 works) · Mathematics (2 works) · Political science (2 works) · The Internet (2 works) · World Wide Web (2 works) · Advertising (1 work) · Art (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Artificial neural network (1 work)