Data modelling for large-scale social media analytics: design challenges and lessons learned

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dc.authoridAydin, Ahmet Arif/0000-0002-4124-7275
dc.authoridAydin, Ahmet Arif/0000-0002-4124-7275
dc.authorwosidAydin, Ahmet Arif/GON-5504-2022
dc.authorwosidAydin, Ahmet Arif/K-6184-2019
dc.contributor.authorAydin, Ahmet Arif
dc.contributor.authorAnderson, Kenneth M.
dc.date.accessioned2024-08-04T20:49:06Z
dc.date.available2024-08-04T20:49:06Z
dc.date.issued2020
dc.departmentİnönü Üniversitesien_US
dc.description.abstractWe live in a world of big data; organisations collect, store, and analyse large volumes of data for various purposes. The five V's of big data introduce new challenges for developers to handle when performing data processing and analysis. Indeed, data modelling is one of the most challenging and critical aspects of big data because it determines how data will be structured and stored; these decisions then impact how that data can be processed and analysed. In this paper, we report on designing a data model for storing and analysing Twitter data in support of crisis informatics. In this work, we leverage the data model provided by columnar NoSQL data stores to design column families that can efficiently index, sort, store and analyse large Twitter datasets. In particular, our column families are designed to achieve efficient batch data processing. We evaluate these claims and discuss our future work.en_US
dc.identifier.doi10.1504/IJDMMM.2020.111409
dc.identifier.endpage414en_US
dc.identifier.issn1759-1163
dc.identifier.issn1759-1171
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85097132144en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage386en_US
dc.identifier.urihttps://doi.org/10.1504/IJDMMM.2020.111409
dc.identifier.urihttps://hdl.handle.net/11616/99655
dc.identifier.volume12en_US
dc.identifier.wosWOS:000596237800002en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInderscience Enterprises Ltden_US
dc.relation.ispartofInternational Journal of Data Mining Modelling and Managementen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdata modellingen_US
dc.subjectsocial media analyticsen_US
dc.subjectbig data analyticsen_US
dc.subjectNoSQLen_US
dc.titleData modelling for large-scale social media analytics: design challenges and lessons learneden_US
dc.typeArticleen_US

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