Diverging patterns of interaction around news on social media: insularity and partisanship during the 2018 Italian election campaign

ABSTRACT

The paper considers how social media ecologies are affecting partisan engagement around political news and online attention economies by investigating the case of the 2018 Italian general election. By analyzing Twitter and Facebook interactions around political news in the lead-up to the election, we shed light on levels of insularity characterizing sources preferred by different partisan communities and investigate how specific patterns of active attention emerge around different sources and around stories proposing different framing of specific political actors. Our findings indicate that, on Twitter, sources mainly shared by supporters of populist parties (the Five Star Movement and the League) are characterized by higher levels of insularity compared to those shared by supporters of other parties. We also find that, on Facebook, news items published by highly insular sources receive a higher number of shares per comment. Finally, our analyses show that news presenting a positive framing of the Five Star Movement – the unique ‘cyber party’ in the system – receives a higher number of shares per comment compared to items presenting the Movement in a negative light, while the opposite is true for stories on all other political parties.     

Simulation analysis of cold chain performance based on time–temperature data

Perishable goods are a fundamental source of revenue for the retail sector; their management, however, constitutes a severe challenge for retailers and supply chain partners. A significant cost in particular is the fraction of products perished through the supply chain, which also constitutes an ethical and environmental concern. Supply chain organisation and operative characteristics have a significant influence on this matter, as in fact ensuring suitable temperature conditions for the stock-keeping units throughout the supply chain is mandatory for perishable products. Recent developments in sensing and communication technologies allow detailed monitoring and control of cold chain; however, depending on the characteristics of the supply chain, an inherent risk of perished products is often inevitable, even in the hypothesis of perfect control. This article proposes a methodology to evaluate the performance of a cold chain in terms of expected product quality at the retail store, and to estimate the expected fraction of perished products, according to the supply chain configuration. The approach is based on Monte Carlo simulation, and implements referenced shelf-life models. A real application is also presented, involving a preliminary analysis and mapping of the supply chain activities based on time–temperature data, in order to demonstrate the practicability of the approach proposed.     

Examining the Incidence and Clients’ Experiences of Single Session Therapy in Italy: A Feasibility Study

Single session therapy (SST) postulates that one session can be sufficient for a client to take charge of the process and work toward their own solutions. Research has been conducted worldwide corroborating SST assumptions with several mental health conditions, but not in Italy. For the first time in Italy, this paper aims to explore: (1) if the most frequent number of sessions in traditional psychotherapy (not SST) is one (Study 1); and (2) the satisfaction of clients who attend SST services and the number who consider one session sufficient to address their presenting problem (Study 2). In Study 1, the records of 476 voluntary clients referred to three different traditional (not SST) psychological services in the west-central region of Latium, Italy, were retrospectively screened, and the number of sessions attended by each client recorded. In Study 2, 85 consecutive clients who voluntarily asked for SST with seven mental health professionals across Italy received a link to an online ad hoc survey, 1–3 weeks after the consultation, evaluating their experience. Study 1 found that the most frequent number of traditional psychotherapeutic (not intentionally SST) sessions was one (124 out of 476 clients (26%). Study 2 found that 44 out of 85 clients (52%) considered one session to be enough, as they felt better or much better and chose not to attend further sessions. Of those who asked for a second session (41 clients), 33 clients (80.5%) indicated that the first session was not enough and 8 clients (19.5%) wanted to address a new problem. These results converge with previous international studies and provide encouragement for the use of SST in both private and public psychological services to address the demand for timely mental health services in Italy. Further research is needed to support the efficacy of SST and to evaluate its cost-effectiveness.     

Including covariates in a space-time point process with application to seismicity

The paper proposes a spatio-temporal process that improves the assessment of events in space and time, considering a contagion model (branching process) within a regression-like framework to take covariates into account. The proposed approach develops the forward likelihood for prediction method for estimating the ETAS model, including covariates in the model specification of the epidemic component. A simulation study is carried out for analysing the misspecification model effect under several scenarios. Also an application to the Italian seismic catalogue is reported, together with the reference to the developed R package.

     

Financial contagion through space-time point processes

Statistical Methods & Applications - We propose to study the dynamics of financial contagion by means of a class of point process models employed in the modeling of seismic contagion. The...     

Construction of a Frailty Indicator with Partially Ordered Sets: A Multiple-Outcome Proposal Based on Administrative Healthcare Data

Social Indicators Research - Given the progressive aging of Italian and European populations, the number of cases with chronic diseases is steeply increasing. This calls for new strategies for...     

Challenging scalar fallacy in state-wide welfare studies: A UK sub-state comparison of civil society approaches to addressing youth unemployment

Here we make an original, empirical contribution to debates on welfare pluralism, the mixed economies of welfare and territorial rescaling by comparing civil society approaches to tackling youth unemployment in England, Scotland and Wales. Our core finding is that academic and policy literature's frequent characterisation of the UK as a single Liberal welfare regime is based on methodological nationalism privileging state-wide analyses. In short, a scalar fallacy pervasive in international welfare studies. In the context of the global rise of meso-government and so-called ‘stateless nations’ pressing for greater autonomy, our case-study challenges the dominant paradigm. Our analysis shows the liberal characteristics of work-first policy orientation and marketised civil society are concentrated in England then tempered by devolved (social) policy. Based on contrasting, left-of-centre and civic nationalist governing traditions, grounded in multi-level electoral politics, we show the devolved nations taking a different approach to Westminster, partially eschewing the market and incorporating collectivism and co-production.     

Migration and students' performance: detecting geographical differences following a curves clustering approach

Students'' migration mobility is the new form of migration: students migrate to improve their skills and become more valued for the job market. The data regard the migration of Italian Bachelors who enrolled at Master Degree level, moving typically from poor to rich areas. This paper investigates the migration and other possible determinants on the Master Degree students'' performance. The Clustering of Effects approach for Quantile Regression Coefficients Modelling has been used to cluster the effects of some variables on the students'' performance for three Italian macro-areas. Results show evidence of similarity between Southern and Centre students, with respect to the Northern ones.     

Change-Point Detection for Variance Piecewise Constant Models

A new approach based on the fit of a generalized linear regression model is introduced for detecting change-points in the variance of heteroscedastic Gaussian variables, with piecewise constant variance function. This approach overcome some limitations of both exact and approximate well-known methods that are based on successive application of search and tend to overestimate the real number of changes in the variance of the series. The proposed method just requires the computation of a gamma GLM with log-link, resulting in a very efficient algorithm even with large sample size and many change points to be estimated.     

Local spatial log-Gaussian Cox processes for seismic data

AStA Advances in Statistical Analysis - In this paper, we propose the use of advanced and flexible statistical models to describe the spatial displacement of earthquake data. The paper aims to...