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AuthorAlajmi, Abdullah
AuthorPetri, Ioan
AuthorRezgui, Yacine
AuthorFadli, Fodil
Available date2024-03-18T08:51:18Z
Publication Date2023-06
Publication NameProceedings of the 29th International Conference on Engineering, Technology, and Innovation: Shaping the Future, ICE 2023
Identifierhttp://dx.doi.org/10.1109/ICE/ITMC58018.2023.10332268
CitationAlajmi, A., Petri, I., Rezgui, Y., & Fadli, F. (2023, June). Social media data analysis of IoT risks in smart cities. In 2023 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1-7). IEEE.
ISBN979-835031517-2
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85181054562&origin=inward
URIhttp://hdl.handle.net/10576/53147
AbstractSocial media has emerged as the most popular platform for individuals from all walks of life who wish to connect with one another to discuss recent news or events that have taken place all over the globe. Twitter, in particular, is among the most important social networks with users that produce real time content. Users can also create a new hashtag or a particular topic to attract other users to enter a discussion. Within the scope of this research project, our goals are to gain an understanding of the effect that social media data has on the Internet of Things (IoT) in smart cities, to provide a description of the risks that have been posed, and to determine whether each individual tweet is neutral, positive, or negative in relation to evaluation criteria. We have conducted research by studying the effects of weather and temperature and how they affect the Internet-of-Things. We use data and scenarios using the World Cup event that took place in Qatar as a prominent example because of the large number of people, services and assets allocated and associated data.
SponsorThis publication was made possible by NPRP grant No. NPRP12S- 0222-190128 from the Qatar National Research Fund (a member of Qatar Foundation).
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc. (IEEE)
SubjectData analysis
IoT Risks
Natural Language Processing
Smart cities
Social media
TitleSocial media data analysis of IoT risks in smart cities
TypeConference
dc.accessType Full Text


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