Change Point Detection in Terrorism-Related Online Content Using Deep Learning Derived Indicators
Given the increasing occurrence of deviant activities in online platforms, it is of paramount importance to develop methods and tools that allow in-depth analysis and understanding to then develop effective countermeasures. This work proposes a framework towards detecting statistically significant c...
Main Authors: | Ourania Theodosiadou, Kyriaki Pantelidou, Nikolaos Bastas, Despoina Chatzakou, Theodora Tsikrika, Stefanos Vrochidis, Ioannis Kompatsiaris |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2078-2489/12/7/274 |
Similar Items
-
A Morpho-syntactic Analysis of Human-moderated Hate Speech Samples from Wykop.pl Web Service
by: Inez Okulska, et al.
Published: (2024-02-01) -
A Literature Review of Textual Hate Speech Detection Methods and Datasets
by: Fatimah Alkomah, et al.
Published: (2022-05-01) -
How can we detect Homophobia and Transphobia? Experiments in a multilingual code-mixed setting for social media governance
by: Bharathi Raja Chakravarthi, et al.
Published: (2022-11-01) -
Terrorism, Tourism and Worker Unions: The disciplinary boundaries of fear
by: Maximiliano Korstanje, et al. -
Hate Speech Detection: Performance Based upon a Novel Feature Detection
by: Saugata Bose
Published: (2022-12-01)