Multidimensional Analyses of Social Media Related Geographic Information: a Study Concerning the Urban Area of Cagliari (Sardinia, Italy)

The widespread diffusion of tourism social media platforms is playing an increasingly important role as information source both for tourists, who gather reliable information supporting destinations’ choice and services from peers, and for businesses, who can use the same information for improving their marketing strategies. The use of this type of information could also offer new opportunities for decision-support in tourism planning. By means of improved understanding of the travel motivations and by tailoring tourism service supply, decision making can be facilitated by emphasising the strengths of tourist destinations for past and potential visitors. However, information about tourists’ perceptions and opinions is not always properly analysed by planners. User satisfaction depends on factors related to the location and the services quality that the local industry proposes. Moreover, its understanding may offer valuable knowledge in tourism planning at the regional and local levels. The goal of the study of the paper is to propose an integrated approach to investigate, qualitatively and quantitatively, the relationships between tourists’ satisfaction, geographic locations and tourist enterprises in supporting decision-making processes. The methodology implemented in the study includes data collection from Booking and TripAdvisor.com and their integration with authoritative territorial data. Spatial and statistical analysis techniques are applied in order to assess tourists’ perceptions on success factors, which may be used as planning support tools. The case study concerns the municipality of Cagliari and demonstrates the value of social media-related data integrated by authoritative information in tourism planning. Finally, the paper proposes a critical discussion on the effectiveness of using the implemented integrated approach in order to address other planning issues. The discussion underlines the potential of the proposed approach in order to address other planning questions as well

Social media data in tourism planning: Analysing tourists satisfaction in space and time.

Social media are playing an increasingly important role as information resource in tourism both for customers (i.e. the tourists), who gather trustworthy information supporting the choice of destinations and services from peers, and for businesses, which can use the same information for improving their marketing strategies. The use of social media data can also offer new opportunities for decision- support in tourism planning. With improved understanding of the motivations of tourists and tailoring tourism service supply, decision making can be facilitated by emphasizing the strengths of tourist destinations for past and potential visitors. However, this kind of information about tourists perceptions and opinions is not always properly analysed by planners. Understanding the user satisfaction, which depend on factors related to both the location and the services that the local industry propose, may offers valuable information in tourism planning at regional and local level. In the light of the above premises, the goal of the study presented in this paper is to propose an integrated approach to investigate the relationships between tourists satisfaction, destination resources and tourism industry for supporting design and decision-making in regional tourism planning. The methodology developed in the study includes data collection from popular tourism social media platforms (i.e. Booking.com and TripAdvisor.com.com), and their integration with territorial and tourism data. Spatial and statistical analysis techniques are then applied to elicit insights from tourists perceptions on success factors which may be used in decision-making and planning support. The case study demonstrates the value of social media data and computational social science techniques in tourism planning. The paper concludes with a critical discussion on the potential of using such an approach in more general urban and regional planning setting

Le informazioni geografiche dei social network (SMGI) a supporto della pianificazione del turismo. L’esempio di Cagliari.

Il contributo propone una discussione sul possibile utilizzo delle informazioni geografiche provenienti dai social network nell’ambito della pianificazione del turismo su scala regionale e locale. Il crescente utilizzo dei social network da parte degli utenti in tutto il mondo ha fatto si che queste piattaforme, e soprattutto l’informazione derivante da esse, sia utile per i turisti, che possono facilmente ottenere dati adeguati sulle destinazioni e sui servizi offerti, grazie alle recensioni liberamente condivise dagli altri utenti, e per gli operatori turistici, i quali possono utilizzare queste informazioni per migliorare le proprie strategie di marketing e promozione. Questi dati, comunemente definiti Social Media Geographic Information (SMGI), possono inoltre offrire nuove opportunità per supportare le fasi decisionali nella pianificazione del turismo. Purtroppo la ricchezza di contenuti sulle percezioni e sulle opinioni degli utenti, resa disponibile dalle SMGI, non viene ancora adeguatamente utilizzata dai pianificatori per le analisi territoriali. Lo studio propone un nuovo approccio per analizzare, qualitativamente e quantitativamente, attraverso l’uso delle SMGI, le relazioni che insistono tra il gradimento dei turisti, le località geografiche e l’offerta turistica in Sardegna. La metodologia adottata include la raccolta di dati da Booking.com e TripAdvisor, la loro integrazione ed elaborazione con i dati ufficiali in ambiente GIS, e l’applicazione di tecniche di analisi di statistica spaziale per identificare e valutare i fattori che possono determinare il successo di una destinazione turistica. La metodologia viene applicata alla scala regionale, individuando le aree maggiormente apprezzate dai turisti, ed alla scala locale per la destinazione di Cagliari, per la quale vengono identificati e valutati i principali fattori che ne determinano il successo come destinazione turistica. I risultati ottenuti possono essere utilizzati come base conoscitiva per guidare ulteriori specifiche analisi e per sviluppare strategie di sviluppo sostenibile nell’ambito della pianificazione territoriale e del turismo tramite processi decisionali informati

SMGI in tourism planning: the role of customers’ preferences in spatial decision support.

The dissertation deals with the role of social media platform is playing as an information resource in tourism both for customers (i.e. the tourists), who gather trustworthy information supporting the choice of destinations and services from peers, and for businesses, which can use the same information for improving their marketing strategies. The use of social media data can also offer new opportunities for decision‐support in tourism planning. With improved understanding of the motivations of tourists and tailoring tourism service supply, decision making can be facilitated by emphasizing the strengths of tourist destinations for past and potential visitors. However, this kind of information about tourists’ perceptions and opinions is not always properly analysed by planners. Understanding the user satisfaction, which depends on factors related to both the location and the services that the local industry proposes, may offer valuable information in tourism planning at regional and local level. In the light of the above premises, the goal of this study is to propose an integrated approach to investigate the relationships between tourists’ satisfaction, destination resources and tourism industry for supporting design and decision‐making in regional tourism planning. The methodology implemented in the thesis includes data collection from Booking and TripAdvisor.com and their integration with authoritative territorial data. Spatial and statistical analysis techniques are applied in order to assess tourists’ perceptions on success factors, which may be used as planning support tools. Four cases study demonstrates the value of social media‐related data integrated by authoritative information in tourism planning. Finally, the dissertation proposes a critical discussion on the effectiveness of using the implemented integrated approach in order to address other planning issues. The discussion underlines the potential of the proposed approach in order to address other planning questions as well

Ground motion areas detection (GMA-D): an innovative approach to identify ground deformation areas using the SAR-based displacement time series

Abstract. In this work, an innovative methodology to generate the automatic ground motion areas mapping is presented. The methodology is based on the analysis of the Synthetic Aperture Radar (SAR)-based displacement time series. The procedure includes two modules developed using the ModelBuilder tool (ArcGis). These modules allow to identify the ground motion areas (GMA) using only one dataset and the persistent GMA (PGMA) considering the different monitored periods and datasets. These areas represent clusters of targets characterized by the same displacement time series trend. The procedure was tested using different sensors such as ERS-1/2, ENVISAT, COSMO-SkyMed and Sentinel-1 covering the periods, 1992–2000, 2003–2010, 2012–2016 and 2014–2017, respectively, over an area of about 500 km2 in the Venetian-Friulian coastal Plain (NE Italy). The resulting mapping allows to detect priority areas where to address further in situ investigations such as to verify the presence of localized buried landforms

Intestinal bacterial flora of Mediterranean gilthead sea bream (Sparus aurata Linnaeus) as a novel source of natural surface active compounds

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Anti-CD74 antibodies have no diagnostic value in early axial spondyloarthritis: Data from the spondyloarthritis caught early (SPACE) cohort

Anti-CD74 IgG antibodies are reported to be elevated in patients with axial spondyloarthritis (axSpA). This study assessed the diagnostic value of anti-CD74 antibodies in patients with early axSpA. Anti-CD74 IgG and IgA antibodies were first measured in an exploratory cohort of patients with radiographic axSpA (138 patients with ankylosing spondyloarthritis (AS)) and 57 healthy controls and then were measured in patients with early axSpA (n = 274) and with non-SpA chronic back pain (CBP) (n = 319), participating in the spondyloarthritis caught early (SPACE) prospective cohort study of patients under 45 years old with early back pain (for ≥ 3 months, but ≤ 2 years). In the exploratory cohort, anti-CD74 IgG antibodies were present in 79.7% of patients with AS vs. 43.9% of healthy controls (p < 0.001). Anti-CD74 IgA antibodies were present in 28.5% of patients with AS vs. 5.3% of healthy controls (p < 0.001). In the SPACE cohort, anti-CD74 IgG antibody levels were present in 46.4% of the patients with axSpA vs. 47.9% of the patients with CBP (p = 0.71). Anti-CD74 IgA antibodies were present in 54.7% of the patients with axSpA and 37.0% of the patients with CBP (p < 0.001). This resulted in a positive predictive value of 58.8% (compared to a prior probability of 46.2%) and a negative predictive value of 59.1% (compared to a prior probability of 53.8%). In a regression model, total serum IgA was associated with axSpA odds ratio (OR) 1.19, p < 0.001) whereas anti-CD74 IgA was not (OR) 1.01, p = 0.33). Furthermore, anti-CD74 IgA was associated with sacroiliitis on magnetic resonance imaging (MRI) (OR) = 2.50, p = 0.005) and heel enthesitis (OR) = 2.56, p = 0.002). Albeit anti-CD74 IgA is elevated in patients with early axSpA, this elevation is not sufficiently specific to yield significant diagnostic value in patients under 45 years old presenting with early back pai

Do quality of life and work productivity change in early axial spondyloarthritis and non-axial spondyloarthritis patients after two years?

© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology.OBJECTIVE: To compare health-related quality of life (HRQoL) and work productivity in axial spondyloarthritis (axSpA) and non-axSpA patients with chronic back pain of < 2 years (2 y). METHODS: Baseline and 2 y data of patients included in the SPondyloArthritis Caught Early cohort were analyzed. HRQoL was assessed by the physical (PCS) and mental component summary (MCS) scores of the 36-Item Short-Form Health Survey; and presenteeism, absenteeism, work productivity loss (WPL) and activity impairment (AI) by the Work Productivity and Activity Impairment questionnaire. Linear or zero-inflated negative binomial regression was conducted to compare 2 y outcomes between groups (axSpA and non-axSpA), adjusting for the baseline value, sex, age and use of nonsteroidal anti-inflammatory drugs. RESULTS: There were 265 axSpA and 108 non-axSpA patients: males 52% vs 26%, mean age 29 vs 31 years, respectively. At baseline, non-axSpA patients showed worse PCS (mean 28.6 axSpA vs 26.6 non-axSpA), presenteeism (31.1% vs 37.3%), absenteeism (8.2% vs 10.3%), WPL (34.7% vs 44.1%) and AI (39.6% vs 48.5%). MCS was not impaired in either group. After 2 y, PCS, presenteeism, WPL and AI significantly improved in both groups; absenteeism only in axSpA. In multivariable analysis, axSpA (vs non-axSpA) was associated with 22% less WPL (incidence rate ratio [95% CI]: 0.78 [0.62; 0.98]) and 18% less AI (0.82 [0.69; 0.97]). CONCLUSION: HRQoL and work productivity are more impaired in non-axSpA (vs axSpA) at baseline and still after 2 y. Although most outcomes improve in both groups, axSpA is associated with larger improvements in work productivity and activity impairment.publishersversionepub_ahead_of_prin