KaydedilenlerDerginizi ekleyin

Dergiler / Yönetim Bilişim Sistemleri Dergisi / 2016 / Cilt: 2 - Sayı: 2

LINGUISTIC STUDIES ON TWEETS GATHERED FROM MUĞLA REGION: A PRELIMINARY STUDY

Feriştah DALKILIÇ
Enis KARAARSLAN
Ali HÜRRİYETOĞLU
Enis KARAARSLAN
Ali HÜRRİYETOĞLU
Sayfa
29–39
Yayın Tarihi
2016-10-19
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

We consider this analysis as a first step to a more detailed and complete study for this region.Keywords: social media analysis, tweet, smart city, crowd sensing

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Citizens or visitors of a city can supply significant information with their social media posts by using mobile devices.
📊
Temel Bulgular & Veri:These data can give information about complaints, touristic attractions, emergency situations etc.
💡
Sonuç & Katkı:We consider this analysis as a first step to a more detailed and complete study for this region.Keywords: social media analysis, tweet, smart city, crowd sensing
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

Citizens or visitors of a city can supply significant information with their social media posts by using mobile devices. These data can give information about complaints, touristic attractions, emergency situations etc. Social media analysis will be beneficial for smart city and smart management concept. This study is a first attempt to analyze and understand this touristic Muğla region by using social media. During this study, a sample dataset is formed by collecting the tweets that were sent from the Muğla region. Linguistic studies are implemented in tweets which are in Turkish language. Various techniques, statistical language and characteristics are used. Preliminary study revealed main topics about the region, user and hashtag types. We consider this analysis as a first step to a more detailed and complete study for this region.Keywords: social media analysis, tweet, smart city, crowd sensing

🔖

Bu Makaleye Atıf Yap

DALKILIÇ, F., KARAARSLAN, E., HÜRRİYETOĞLU, A., KARAARSLAN, E., HÜRRİYETOĞLU, A. (2016). LINGUISTIC STUDIES ON TWEETS GATHERED FROM MUĞLA REGION: A PRELIMINARY STUDY. Yönetim Bilişim Sistemleri Dergisi, Cilt: 2 - Sayı: 2, 29–39. https://ajindex.com/articles/823554

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (11)

  1. Anantharam, P., Barnaghi, P., Thirunarayan, K., and Sheth, A. (2015). Extracting city traffic events from social streams. ACM Transactions on Intelligent Systems and Technology (TIST), 6(4), 43. Bakıcı, T., Almirall, E., and Wareham, J. (2013). A smart city initiative: the case of Barcelona. Journal of the Knowledge Economy, 4(2), 135-148.
  2. Bowerman, B., et al. "The vision of a smart city." 2nd International Life Extension Technology Workshop, Paris. Vol. 28. 2000.
  3. Cavazos-Rehg, P.A., Krauss, M.J., Sowles, S., Connolly, S., Rosas, C., Bharadwaj, M., and Bierut, L.J. (2016). A content analysis of depression-related tweets. Computers in Human Behavior, 54: 351-357.
  4. Demirci, S. (2014). Emotion Analysis On Turkish Tweets. M.Sc. Thesis, Middle East Technical University, Ankara.
  5. Friedman, W. (1922). The Index of Coincidence and Its Applications in Cryptography. Publication No. 22. Geneva IL: Riverbank Publications. Ilina, E., Hauff, C., Celik, I., Abel, F., and Houben, G.J. (2012). Social event detection on twitter. In Web Engineering (pp. 169-176). Springer Berlin Heidelberg. INFOSEC Institute, Crowdsensing: State of the Art and Privacy Aspects, http://resources.infosecinstitute.com/crowdsensing-state-art-privacy-aspects/, 2014.
  6. Kit, C., and Wilks, Y. (1998). The Virtual Approach to Deriving Ngram Statistics from Large Scale Corpora. International Conference on Chinese Information Processing Conference, Beijing, China, pp. 223—229. Kunneman, F., Hürriyetoğlu, A., Oostdijk, N., and van den Bosch, A. (2014). Timely identification of event start dates from Twitter. Computational Linguistics in the Netherlands Journal, 4: 39-52.
  7. Leung, D., Law, R., Van Hoof, H., and Buhalis, D. (2013). Social media in tourism and hospitality: A literature review. Journal of Travel & Tourism Marketing, 30(1-2), 3-22.
  8. Menezes, A., van Oorschot, P. and Vanstone, S. (1996). Handbook of Applied Cryptography. CRC Press.
  9. Mohammad, S.M., and Kiritchenko, S. (2015). Using Hashtags to Capture Fine Emotion Categories From Tweets. Computational Intelligence, 31 (2): 301-326.
  10. Örücü, F. (2009). Turkish Language Characteristics And Author Identification. M.Sc. Thesis, Dokuz Eylül University, İzmir.
  11. Preece, A., Webberley, W., and Braines D. (2015). Tasking the tweeters: Obtaining actionable information from human sensors. SPIE Defense+ Security. International Society for Optics and Photonics. Quercia, D., Schifanella, R., and Aiello, L.M. (2014). The shortest path to happiness: Recommending beautif