Temporal Sentiment Analysis of Socially Important Locations of Social Media Users
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Socially 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.
Açıklama
5th International Conference on Smart City Applications, SCA 2020 -- 7 October 2020 through 9 October 2020 -- Karabuk -- 255519
Anahtar Kelimeler
Sentiment at socially important locations, Social media mining, Temporal sentiment analysis, Twitter
Kaynak
Lecture Notes in Networks and Systems
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
183
