Recommendation Systems on Twitter Data for Marketing Purposes using Content-Based Filtering

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dc.contributor.authorAlbayati, A.N.K.
dc.contributor.authorOrtakci, Y.
dc.date.accessioned2024-09-29T16:20:55Z
dc.date.available2024-09-29T16:20:55Z
dc.date.issued2022
dc.departmentKarabük Üniversitesien_US
dc.description4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2022 -- 9 June 2022 through 11 June 2022 -- Ankara -- 180434en_US
dc.description.abstractWith artificial intelligence and machine learning enhancement over time, many concepts in commerce and marketing have changed. Today, many people are using online shopping options since online platforms provide a wide variety of products. Vendors also try to attract customers and offer them user-specific products on online shopping platforms using many technologies. One of these technologies is Recommendation Systems (RS) which makes information filtering on batch data. RS makes shopping very easy for both customers and vendors. While it suggests products they may like or prefer for customers, it also provides a target customer list for vendors. RS can also be applied to many social media platforms for marketing purposes. In this paper, we propose an RS analyzing Twitter data for vendors. In our RS, vendors search some keywords to extract target Twitter users as customers, and then it lists the corresponding Twitter users using the Content-Based Filtering technique. Our systems succeeded to recommend the target customer list with 86. 24 % accuracy. © 2022 IEEE.en_US
dc.identifier.doi10.1109/HORA55278.2022.9799989
dc.identifier.isbn978-166546835-0
dc.identifier.scopus2-s2.0-85198689942en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/HORA55278.2022.9799989
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9427
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofHORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectContent-based filteringen_US
dc.subjectNLPen_US
dc.subjectRecommendation systemsen_US
dc.subjectTwitteren_US
dc.titleRecommendation Systems on Twitter Data for Marketing Purposes using Content-Based Filteringen_US
dc.typeConference Objecten_US

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