Venera Tomaselli

Building Tourism Networks through Tourist Mobility

This article aims to define tourism networks analyzing tourist mobility between destinations. The study adopts network analysis methods, testing a data processing strategy that combines descriptive measurements and clustering tools. A segmentation approach has been employed to investigate differences or similarities between the trip-related attributes of tourists within networks. Data are from a sampling survey carried out on tourists’ visit in Sicily. The results show that the tourist choice defined the role of a destination as “central” or “peripheral” within a network. Tourists build their own networks around nodal destinations, even if they are geographically distant. Thus, tourist mobility affects the shape, the dimension, and the structure of the networks, where tourists are different for characteristics, trip-related behaviors, and type of holiday chosen. The study provides some evidence that can be useful for planning tourism facilities, managing tourism routes, and defining destination management strategies.

Frequency of Use and Smoking Status of U.S. Adolescent E-Cigarette Users in 2015

INTRODUCTION E-cigarette use by adolescents is an important issue for public health. This study analyzed the frequency of e-cigarette use and its association with smoking status among U.S. adolescents. METHODS The National Youth Tobacco Survey 2015 was analyzed in 2017, focusing on frequency of past 30-day e-cigarette use according to smoking status of participants. Smoking status was classified as never smoker, ever/not a past 30-day smoker, and past 30-day smoker. Infrequent and frequent smoking and e-cigarette use was defined as use for <20 and ≥20 of the past 30 days, respectively. RESULTS Past 30-day e-cigarette use was reported by 54.5% (95% CI=47.8%, 61.0%) of past 30-day smokers, 26.5% (95% CI=23.2%, 30.1%) of ever/not past 30-day smokers, and 4.6% (95% CI=4.0%, 5.2%) of never smokers (p<0.001). No past 30-day e-cigarette use was reported by 94.5% and frequent e-cigarette use by 0.3% of never smokers. Past 30-day e-cigarette use was reported by 50.4% (95% CI=43.6%, 57.3%) of infrequent and 64.7% (95% CI=54.4%, 73.8%) of frequent past 30-day smokers (p<0.001). E-cigarette use frequency correlated with both smoking status and tobacco cigarette consumption (ρ=0.42, p<0.001 and ρ=0.40, p<0.001, respectively). Past 30-day smokers were more likely to report past 30-day e-cigarette use (OR=11.42, 95% CI=9.06, 14.40) compared with adolescents reporting no past 30-day smoking. CONCLUSIONS E-cigarette use is more prevalent among ever and past 30-day smoking adolescents compared with never smoking adolescents. Frequent e-cigarette use is rare among never smoking adolescents.

Research Note: Analysing tourism demand in tourist districts – the case of Sicily

This paper analyses tourism demand in the tourist districts in Sicily to study the relationship between the characteristics of tourists, types of tourism and expenditure. The data were obtained from a survey of tourists leaving the island after a holiday. The likelihood of choosing a type of holiday is estimated by means of a multinomial logistic model. The findings highlight the importance of the seaside, cultural, and food and wine/nature segments. The analysis of the distribution of per capita per day expenditure shows higher average values for the cultural holiday. The research provides insights for decision makers concerning the implementation of destination market strategies.

Network Analysis Methods for Classification of Roles

This paper concerns network analysis (NA) methods employed to classify role profiles based on the measurement and the specification of linking structures among pupils in infant school. With this aim, we measure sociometric status by the direct observation of preschool children behaviours. The data have been collected by a longitudinal observational study. We follow the children in seven waves for 2 months. In this study, we measure relational skills of subjects applying three procedures: The regular equivalence is used to detect similar positions within the network, the lambda sets to observe the ability to be intermediary and the cliques to assess the propensity to belong to a group. Concerning each analytic dimension, the results show an increase of relational competence and an association with ego-network measures.

Big Data and Network Analysis: A Promising Integration for Decision-Making

In recent years, we have witnessed an extraordinary growth in globally generated data. The automatic extraction of such extraordinary amount of data, together with innovative data mining and predictive analytics techniques, represents an innovative opportunity in supporting decision-making. Thus, the main aim of this paper is to explore the opportunity of integrating Big Data techniques with Network Analysis methods. In particular, our study employs descriptive measurements and clustering methods of Network Analysis in order to define relational structures within a Big Data set. We discuss a Big Data tool that collects and analyses information from user interactions with published news and comments about a case study related to a recent Italian constitutional review bill with important political implications.

Meta-Analysis of Poll Accuracy Measures: A Multilevel Approach

Following a meta-analysis approach as a special case of multilevel modelling, we identify potential sources of dissimilarities in accuracy measures of pre-election polls, carried out during Parliamentary elections in Italy from 2001 to 2008. The predictive accuracy measure, computed to compare the pre-electoral poll result to the actual result, is the dependent variable and the poll characteristics are the explanatory variables and are introduced in a hierarchical model. In the model each outcome is affected by a specific sampling error assumed to have a normal distribution and a known variance. The multilevel model approach decomposes variance components as well as meta-analysis random models. We propose a multilevel approach, in order to make the estimation procedure easier and more flexible than in a traditional meta-analysis approach.

Classifying Tourism Destinations: An Application of Network Analysis

Tourism is basically a spatial phenomenon, which implies moving consumption within space. Starting from the assumption that the destinations are nodes of a network, we are able to reconstruct a spatial grid where each locality shows different grades and types of centrality. The analysis, focusing on the spatial dimension, shows clusters of locations. By shifting interest from single locations to destination networks, the study points out the structural features of each network. Employing traditional network analysis measures, we classify destinations considering the routes of a self-organized tourists sample that visited more than one destination in Sicily.

Le donne alle primarie: partecipazione politica e reti di attivazione

This contribution aims at analyzing voters’ characteristics and their preference motivations at the first Italian national primary elections in 2005 and the Sicilian regional primary elections in 2006. This analysis mainly focuses on gender differences and is based on a sample of face-to-face interviews. In 2005 the primary elections were called in order to select the centre-left coalition candidate for the following parliamentary elections, while the 2006 ones in order to choose the president of the Sicily region. Several differences between these two primary votes are to be detected, first of all the fact that the regional primaries were much more competitive. Both elections are analyzed by focusing on the voters’ propensity for political and civic involvement with a specific gender-oriented perspective. Political engagement’s mechanisms are reconstructed, allowing to single out different participatory profiles. Furthermore, voting motivation and priorities, cognitive dimensions as well as political communication tools employed by the candidates are considered in order to provide a more accurate explanation of voters’ behavior and attitudes.

Using Multilevel Models to Analyse the Context of Electoral Data

Multilevel models are used to analyse contextual effects in hierarchical structures in order to explore the relationship among nested units. This study aims to observe the link among the territorial micro units nested in higher levels. We examine electoral data in two stages, defined in first level units inside nested structures. In these we used economic, demographic and social variables in order to characterize the context and explore its effects upon the electoral outline of territorial units.

Multivariate statistical techniques and sociological research

Both the validity and the reliability of the statistical techniques used in data processing procedures constitute an important issue concerning the validity of inferences. A critical analysis developed on the data processing techniques takes into account both their correct application and their ability to provide information from which to draw inferences with a testable relationship of correspondence between a piece of information and an inferred sentence. This paper proposes an attempt to test the use of factorial techniques used to construct indicators and of scaling techniques in order to determine semantic areas in the sociological research praxis.