Twitter for election forecasts: a Joint Machine Learning and Complex Network approach applied to an italian case study (Rapporti tecnici/preprint/working paper)

Type

• Prodotto della ricerca (Classe)
• Rapporti tecnici/preprint/working paper (Classe)

Label

• Twitter for election forecasts: a Joint Machine Learning and Complex Network approach applied to an italian case study (Rapporti tecnici/preprint/working paper) (literal)

Anno

• 2015-01-01T00:00:00+01:00 (literal)

Alternative label

• Coletto M., Lucchese C., Orlando S., Raffaele P., Chessa A., Puliga M. (2015)
  Twitter for election forecasts: a Joint Machine Learning and Complex Network approach applied to an italian case study
  
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Coletto M., Lucchese C., Orlando S., Raffaele P., Chessa A., Puliga M. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali

• 4 (literal)

Note

• PuMa (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#supporto

• Altro (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; Università di Venezia, Italy; CNR-ISTI, Pisa, Italy; IMT - Lucca Institute for Advanced Studies, Lucca, Italy; IMT - Lucca Institute for Advanced Studies, Lucca, Italy (literal)

Titolo

• Twitter for election forecasts: a Joint Machine Learning and Complex Network approach applied to an italian case study (literal)

Abstract

• Several studies have shown how to approximately predict real-world phenomena, such as political elections, by ana- lyzing user activities in micro-blogging platforms. This ap- proach has proven to be interesting but with some limita- tions, such as the representativeness of the sample of users, and the hardness of understanding polarity in short mes- sages. We believe that predictions based on social network analysis can be significantly improved by exploiting machine learning and complex network tools, where the latter pro- vides valuable high-level features to support the former in learning an accurate prediction function. (literal)

Prodotto di

• Sistemi e algoritmi per Big Data (ICT.P09.006.001) (Modulo)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)

Autore CNR

• SALVATORE ORLANDO (Persona)
• CLAUDIO LUCCHESE (Persona)
• RAFFAELE PEREGO (Unità di personale interno)

Insieme di parole chiave

• Parole chiave di "Twitter for election forecasts: a Joint Machine Learning and Complex Network approach applied to an italian case study" (Insieme di parole chiave)

Incoming links:

Autore CNR di

• RAFFAELE PEREGO (Unità di personale interno)
• CLAUDIO LUCCHESE (Persona)
• SALVATORE ORLANDO (Persona)
• http://www.cnr.it/ontology/cnr/individuo/unitaDiPersonaleEsterno/ID23654

Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Sistemi e algoritmi per Big Data (ICT.P09.006.001) (Modulo)

Insieme di parole chiave di

• Parole chiave di "Twitter for election forecasts: a Joint Machine Learning and Complex Network approach applied to an italian case study" (Insieme di parole chiave)