Deep Learning-based Sentiment Analysis of Facebook Data: The Case of Turkish Users

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dc.authoridOzel, Selma Ayse/0000-0001-9201-6349
dc.contributor.authorCoban, Onder
dc.contributor.authorOzel, Selma Ayse
dc.contributor.authorInan, Ali
dc.date.accessioned2025-01-06T17:43:50Z
dc.date.available2025-01-06T17:43:50Z
dc.date.issued2021
dc.description.abstractSentiment analysis (SA) is an essential task for many domains where it is crucial to know users' public opinion about events, products, brands, politicians and so on. Existing works on SA have concentrated on English texts including Twitter feeds and user reviews on hotels, movies and products. On the other hand, Facebook, as an online social network (OSN), has attracted quite limited attention from the research community. Among these, SA work on Turkish text obtained from OSNs are extremely scarce. In this paper, our aim is to perform SA on public Facebook data collected from Turkish user accounts. Our study differs from existing studies in terms of the data set scale, the natural language of the texts in the data set and the extent of experimental analyses that include both machine learning and deep learning techniques. We extensively report not only the results of different learning models involving SA but also statistical distribution of metadata of user activities across various user attributes (e.g. gender and age). Our experimental results indicate that recurrent neural networks achieve the best accuracy (i.e. 0.916) with word embeddings. To the best of our knowledge, this is the best result for SA on Facebook data in the context of the Turkish language.
dc.identifier.doi10.1093/comjnl/bxaa172
dc.identifier.endpage499
dc.identifier.issn0010-4620
dc.identifier.issn1460-2067
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85105500627
dc.identifier.scopusqualityQ2
dc.identifier.startpage473
dc.identifier.urihttps://doi.org/10.1093/comjnl/bxaa172
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2824
dc.identifier.volume64
dc.identifier.wosWOS:000644547300015
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherOxford Univ Press
dc.relation.ispartofComputer Journal
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectonline social networks
dc.subjectFacebook
dc.subjectsentiment analysis
dc.subjectmachine learning
dc.subjectdeep learning
dc.titleDeep Learning-based Sentiment Analysis of Facebook Data: The Case of Turkish Users
dc.typeArticle

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