KaydedilenlerDerginizi ekleyin

Dergiler / Gazi University Journal of Science Part A: Engineering and Innovation / 2022 / Cilt: 9 - Sayı: 3

Detecting Turkish Fake News Via Text Mining to Protect Brand Integrity

Özge DOĞUÇ
Sayfa
323–333
Yayın Tarihi
2022-10-19
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)

This is the first study in the literature that introduces an ML model that can accurately identify fake news in Turkish language.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Fake news has been in our lives as part of the media for years.
📊
Temel Bulgular & Veri:Therefore, while companies seek to increase their own brand awareness, they should also protect their brands against fake news spread on social networks and traditional media.
💡
Sonuç & Katkı:This is the first study in the literature that introduces an ML model that can accurately identify fake news in Turkish language.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Text Mining · Fake News · Brand Management

Abstract

Fake news has been in our lives as part of the media for years. With the recent spread of digital news platforms, it affects not only traditional media but also online media as well. Therefore, while companies seek to increase their own brand awareness, they should also protect their brands against fake news spread on social networks and traditional media. This study discusses a solution that accurately classifies the Turkish news published online as real and fake. For this purpose, a machine learning model is trained with tagged news. Initially, the headlines were analyzed within the scope of this study that are collected from Turkish online sources. As a next step, in addition to the headlines of these news, news contexts are also used in the analysis. Analysis are done with unigrams and bigrams. The results show 95% success for the headlines and 80% for the texts for correctly classifying the fake Turkish news articles. This is the first study in the literature that introduces an ML model that can accurately identify fake news in Turkish language.

🔖

Bu Makaleye Atıf Yap

DOĞUÇ, Ö. (2022). Detecting Turkish Fake News Via Text Mining to Protect Brand Integrity. Gazi University Journal of Science Part A: Engineering and Innovation, Cilt: 9 - Sayı: 3, 323–333. https://ajindex.com/articles/520446

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (7)

  1. Ahmed, H., Traore, I., & Saad, S. (2017, October 26-28). Detection of Online Fake News Using N-Gram Analysis and Machine Learning Techniques. In: I. Traore, I. Woungang & A. Awad (Eds.), Intelligent, Secure, and Dependable Systems in Distributed and Cloud Environment, First International Conference, ISDDC 2017,
  2. Vancouver, BC, Canada, (pp. 127–138). doi:10.1007/978-3-319-69155-8_9 Albahar, M. (2021). A hybrid model for fake news detection: Leveraging news content and user comments in fake news. IET Information Security, 15(2), 169–177. doi:10.1049/ise2.12021
  3. Altunbey Özbay, F., & Alataş, B. (2020). Çevrimiçi sosyal medyada sahte haber tespiti. DÜMF Mühendislik Dergisi, 11(1), 91–103. doi:10.24012/dumf.629368 Aytaç, Ö. B., Silahtaroğlu, G., & Doğuç, Ö. (2020). Analysis of Digital Marketing Strategies of Deposit Banks in Turkey via Text Mining Twitter Posts. In: H. Dincer & S. Yüksel (Eds.) Strategic Outlook for Innovative Work Behaviours (pp. 361–376). Springer. doi:10.1007/978-3-030-50131-0_20 Bankole, O., & Reyneke, M. (2020). The Effect of Fake News on the Relationship between Brand Equity and Consumer Responses to Premium Brands: An Abstract. In: S. Wu, F. Pantoja & N. Krey (EdS.), Marketing Opportunities and Challenges in a Changing Global Marketplace (pp. 461–462). Springer International Publishing. doi:10.1007/978-3-030-39165-2_189 Becker, R. (2017, June 26). Your short attention span could help fake news spread. https://www.theverge.com/2017/6/26/15875488/fake-news-viral-hoaxes-bots-information-overload-twitter-facebook-social-media
  4. Belin, A. (2020, June 25). How to Protect and Defend your Brand from Fake News. https://latana.com/post/fake-news-brands/
  5. Chen, Z. F., & Cheng, Y. (2019). Consumer response to fake news about brands on social media: the effects of self-efficacy, media trust, and persuasion knowledge on brand trust. Journal of Product & Brand Management, 29(2), 188–198. doi:10.1108/JPBM-12-2018-2145
  6. Chu, S. K. W., Xie, R., & Wang, Y. (2021). Cross-Language Fake News Detection. Data and Information Management, 5(1), 100–109. doi:10.2478/dim-2020-0025
  7. Conroy, N. K., Rubin, V. L., & Chen, Y. (2015, November 6-10). Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Science and Technology (ASIS&T), 52(1), 1-4. doi:10.1002/pra2.2015.145052010082 de Souza, M. C., Nogueira, B. M., Rossi, R. G., Marcacini, R. M., dos Santos, B. N., & Rezende, S. O. (2021). A network-based positive and unlabe