Semantic Scholar
Open Access
2019
37 sitasi
Fake News Detection: An Interdisciplinary Research
Xinyi Zhou
R. Zafarani
Abstrak
The explosive growth of fake news and its erosion to democracy, journalism and economy has increased the demand for fake news detection. To achieve efficient and explainable fake news detection, an interdisciplinary approach is required, relying on scientific contributions from various disciplines, e.g., social sciences, engineering, among others. Here, we illustrate how such multidisciplinary contributions can help detect fake news by improving feature engineering, or by providing well-justified machine learning models. We demonstrate how news content, news propagation patterns, and users’ engagements with news can help detect fake news.
Topik & Kata Kunci
Penulis (2)
X
Xinyi Zhou
R
R. Zafarani
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2019
- Bahasa
- en
- Total Sitasi
- 37×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1145/3308560.3316476
- Akses
- Open Access ✓