GNGTS 2016 - Atti del 35° Convegno Nazionale

GNGTS 2016 S essione 2.3 445 variability among scores observed and correlated variables, in terms of a potentially lower number of variables called factors. Considering the principal components of each indicator (Hazard, Exposure, Vulnerability, People and Community), we described these components and obtained useful indications to design activities that may improve seismic risk perception. By this method, we think to realize an educational design able to valorise those factors that promote social change for risk reduction. Factor analysis results. We used the 2015 version of the IBM SPSS Statistics (SPSS) to execute an exploratory factor analysis. Factor analysis was executed for every indicator of the SRPQ to identify the principal components that explain the variance for each of indicators considered. The results obtained by the factor analysis (FA) for each indicator indicate that: • ������� �� ��� ��������� ��� ����������� ��� ����� ��� �� ��������� �� ��� ����������� Hazard. FA has indicated two components. The first can be connected to the power/force and size of the earthquake. The second component regards its forecast/not forecast (Fig. 1 and Tab. 1); Tab. 1 – Hazard Factor Analysis: components matrix rotated.       Componente 1 2 Inatteso (1) atteso (7) ,709 -,119 Debole (1) forte (7) ,816 ,175 Piccolo (1) grande (7) ,822 ,167 Lontano (1) vicino (7) ,768 ,091 Prevedibile (1) imprevedibile (7 -,078 ,871 Corto (1) lungo (7) ,696 ,214 Moderato (1) violento (7) ,748 ,300 Lento (1) rapido (7) ,332 ,569 Innocuo (1) pericoloso (7) ,640 ,329 Lontano nel tempo (1) vicino nel tempo (7) ,664 ,026 • ��� �������� �� ��� ��������� ��� ����������� ��� ����� ��� �� ��������� �� �������� For Exposure FA has indicated two components. The first can be connected to care/not care of the territory. The second one to the number of people that frequent it (Fig. 2 and Tab. 2); Fig. 2 – Exposure scree plot.