Known as the 'city of Sassi', Matera underwent a renewal process involving all of the Basilicata regions in the last few years. The city's Tourism resources were almost unknown at a national and international level, although the Sassi were included in the UNESCO World Heritage List since 1993. The European Capital of Culture 2019 nomination triggered an intense regeneration, opening the city to global tourism and revealing a high resilience. Tourists' experiences and opinions have been valuable resources for designing tourism activities and creating a new symbolic identity for the city, especially in the Web 2.0 era. Here we propose to compute the reviews' polarity scores and use them with other characteristics (e.g., price, offered services and type of tourist facilities) to build spatial clusters according to the logic of Local Spatial Association Indicators (LISA). The geo-referenced semantic orientation of reviews concerning a particular activity or attraction represents a useful quantitative feature for further analyses and the production of territorial statistics. The proposal can be extended to other cases to monitor the change of sentiment towards specific areas of interest and plan possible intervention policies.
Geo-referenced sentiment analysis for tourists' points of interest: the case of Matera European Capital of Culture
Michelangelo Misuraca
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2024-01-01
Abstract
Known as the 'city of Sassi', Matera underwent a renewal process involving all of the Basilicata regions in the last few years. The city's Tourism resources were almost unknown at a national and international level, although the Sassi were included in the UNESCO World Heritage List since 1993. The European Capital of Culture 2019 nomination triggered an intense regeneration, opening the city to global tourism and revealing a high resilience. Tourists' experiences and opinions have been valuable resources for designing tourism activities and creating a new symbolic identity for the city, especially in the Web 2.0 era. Here we propose to compute the reviews' polarity scores and use them with other characteristics (e.g., price, offered services and type of tourist facilities) to build spatial clusters according to the logic of Local Spatial Association Indicators (LISA). The geo-referenced semantic orientation of reviews concerning a particular activity or attraction represents a useful quantitative feature for further analyses and the production of territorial statistics. The proposal can be extended to other cases to monitor the change of sentiment towards specific areas of interest and plan possible intervention policies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.