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dc.contributor.authorGarcia, Fabio
dc.contributor.authorBorghini, Francesco
dc.contributor.authorLombardi, Mara
dc.contributor.authorCanfora, Sapienza
dc.contributor.authorRamalingam, Soodamani
dc.date.accessioned2021-12-13T13:00:01Z
dc.date.available2021-12-13T13:00:01Z
dc.date.issued2021-10-15
dc.identifier.citationGarcia , F , Borghini , F , Lombardi , M , Canfora , S & Ramalingam , S 2021 , ' Emotional analysis of safeness and risk perception of London and Rome railway stations during the COVID-19 pandemic ' , Paper presented at IEEE ICCST 2021: 54th IEEE International Carnahan Conference on Security Technology , Hatfield , United Kingdom , 11/10/21 - 15/10/21 .
dc.identifier.citationconference
dc.identifier.urihttp://hdl.handle.net/2299/25252
dc.description© 2021 IEEE.
dc.description.abstractThe evaluation of perceived safeness and risk by persons is particularly valuable for safety and security handling. Each individual is influenced by others’ opinions on safety and security and the Internet embodies the place where these opinions are mostly pursued, acquired, and estimated. From this point of view, social networks play a considerable influential role. For this reason, Opinion Mining and Sentiment Analysis have found noteworthy uses in a variety of situations and one of the most interesting is embodied by public safety and security. The goal of this work is to examine the perception of safety and risk within the railway stations of London (UK) and Rome (Italy) during COVID-19 pandemic. In particular, the railway stations of London Victoria and Waterloo and the railway stations of Rome Termini and Tiburtina were considered, from March 23 to July 9, 2020, highlighting the emotional components in three distinct pandemic phases of the considered period in the two countries, by means of the semantic analysis of the textual contents present in Twitter.en
dc.format.extent6
dc.format.extent1074275
dc.language.isoeng
dc.titleEmotional analysis of safeness and risk perception of London and Rome railway stations during the COVID-19 pandemicen
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionCommunications and Intelligent Systems
dc.contributor.institutionSmart Mobility Unit
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Engineering and Technology
dc.description.statusPeer reviewed
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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