Accepted Papers
We are pleased to present the following accepted papers:
- Social contagion in ethnic abusive swearing during periods of increased terrorist activity. Christoph Spörlein.
- Neural Character-based Composition Models for Abuse Detection. Pushkar Mishra, Helen Yannakoudakis and Ekaterina Shutova. (pdf)
- Hate Speech Dataset from a White Supremacy Forum. Ona de Gibert, Naiara Perez, Aitor García Pablos and Montse Cuadros. (pdf)
- A review of standard text classification practices for multi-label toxicity identification of online content. Isuru Gunasekara and Isar Nejadgholi. (pdf)
- Predictive Embeddings for Hate Speech Detection on Twitter. Rohan Kshirsagar, Tyrus Cukuvac, Kathy McKeown and Susan McGregor. (pdf)
- Challenges for Toxic Comment Classification: An In-Depth Error Analysis. Betty van Aken, Julian Risch, Ralf Krestel and Alexander Löser. (pdf)
- Aggression Detection on Social Media Text Using Deep Neural Networks. Vinay Singh, Aman Varshney, Syed Sarfaraz Akhtar, Deepanshu Vijay and Manish Shrivastava. (pdf)
- Creating a WhatsApp Dataset to Study Pre-teen Cyberbullying. Rachele Sprugnoli, Stefano Menini, Sara Tonelli, Filippo Oncini and Enrico Piras. (pdf)
- Improving Moderation of Online Discussions via Interpretable Neural Models. Andrej Švec, Matúš Pikuliak, Marian Simko and Maria Bielikova. (pdf)
- Aggressive language in an online hacking forum. Andrew Caines, Sergio Pastrana, Alice Hutchings and Paula Buttery. (pdf)
- The Effects of User Features on Twitter Hate Speech Detection. Elise Fehn Unsvåg and Björn Gambäck. (pdf)
- Interpreting Neural Network Hate Speech Classifiers. Cindy Wang. (pdf)
- Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks. Rijul Magu and Jiebo Luo. (pdf)
- Comparative Studies of Detecting Abusive Language on Twitter. Younghun Lee, Seunghyun Yoon and Kyomin Jung. (pdf)
- Boosting Text Classification Performance on Sexist Tweets by Text Augmentation and Text Generation Using a Combination of Knowledge Graphs. Sima Sharifirad, Borna Jafarpour and Stan Matwin. (pdf)
- Learning Representations for Detecting Abusive Language. Magnus Sahlgren, Tim Isbister and Fredrik Olsson. (pdf)
- Datasets of Slovene and Croatian Moderated News Comments. Nikola Ljubešić, Tomaž Erjavec and Darja Fišer. (pdf)
- Cross-Domain Detection of Abusive Language Online. Mladen Karan and Jan Šnajder. (pdf)
- Did you offend me? Classification of Offensive Tweets in Hinglish Language. Puneet Mathur, Ramit Sawhney, Meghna Ayyar, Rajiv Ratn Shah. (pdf)
- Decipherment for Adversarial Offensive Language Detection. Zhelun Wu, Nishant Kambhatla and Anoop Sarkar. (pdf)
- The Linguistic Ideologies of Deep Abusive Language Classification. Michael Castelle. (pdf)