Temporal Sentiment Analysis of Socially Important Locations of Social Media Users

Basit Öğe Kaydı
dc.contributor.authorEcemiş, Alper
dc.contributor.authorDokuz, Ahmet Şakir
dc.contributor.authorCelik, Mete
dc.date.accessioned2024-11-07T10:39:31Z
dc.date.available2024-11-07T10:39:31Z
dc.date.issued2021
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description5th International Conference on Smart City Applications, SCA 2020 -- 7 October 2020 through 9 October 2020 -- Karabuk -- 255519
dc.description.abstractSocially important locations are the places which are frequently visited by social media users. Temporal sentiment analysis of socially important locations is the process of interpretation and classification of emotions within their sharings in their socially important locations over time. Observing the temporal sentiment changes in these locations helps both to examine the emotion change in the locations and to understand the thoughts of the social media users in these locations. In this paper, Twitter is selected as social media data source and temporal sentiment analysis of socially important locations of social media users are analyzed in different time frames. For the analysis, a method, called Temporal Sentiment Analysis of Socially Important Locations (TS-SIL), is proposed in this study. In this method, first of all, socially important locations are discovered from the collected Twitter dataset. Then, sentiment analysis is performed using a dictionary based approach and several machine learning algorithms. Finally, the sharings in the locations are listed and the sentiments at these locations are analyzed by daily, weekly, and monthly basis. As a result, socially important locations of the city of Istanbul are discovered and temporal sentiment analysis of these locations are performed. Results shows that all of the socially important locations of İstanbul, except Beşiktaş Fish Market, showed emotional fluctuations over the time. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
dc.identifier.doi10.1007/978-3-030-66840-2_1
dc.identifier.endpage16
dc.identifier.isbn978-303066839-6
dc.identifier.issn2367-3370
dc.identifier.scopus2-s2.0-85102613136
dc.identifier.scopusqualityQ4
dc.identifier.startpage3
dc.identifier.urihttps://doi.org/10.1007/978-3-030-66840-2_1
dc.identifier.urihttps://hdl.handle.net/11480/11031
dc.identifier.volume183
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofLecture Notes in Networks and Systems
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectSentiment at socially important locations
dc.subjectSocial media mining
dc.subjectTemporal sentiment analysis
dc.subjectTwitter
dc.titleTemporal Sentiment Analysis of Socially Important Locations of Social Media Users
dc.typeConference Object

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu