In recent years, large volumes of data are generated by automatic extraction of information, innovative data mining, and predictive analytics. This paper proposes an innovative approach by combining Big Data with the analysis of relational structures in order to improve actionable analytics-driven decision pat- terns. From the website of one of the largest online Italian newspapers, interactions among users and their comments about a 2016 Italian constitutional review bill are organized in a Big Data audience model. Readers’ sentiments are measured and relational patterns are classified by descriptive measurements and clustering structures implemented in Network Analysis methods.
|Titolo:||Big Data and network analysis: A combined approach to model online news|
TOMASELLI, Venera (Corresponding)
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|