Automatic Detection of Cyberbullying in Social Media Text

While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful prevention depends on the adequate detection of potentially harmful messages and the information overload on the Web requires intelligent systems to identify potential risks automatically. The focus of this paper is on automatic cyberbullying detection in social media text by modelling posts written by bullies, victims, and bystanders of online bullying. We describe the collection and fine-grained annotation of a training corpus for English and Dutch and perform a series of binary classification experiments to determine the feasibility of automatic cyberbullying detection. We make use of linear support vector machines exploiting a rich feature set and investigate which information sources contribute the most for this particular task. Experiments on a holdout test set reveal promising results for the detection of cyberbullying-related posts. After optimisation of the hyperparameters, the classifier yields an F1-score of 64% and 61% for English and Dutch respectively, and considerably outperforms baseline systems based on keywords and word unigrams.Comment: 21 pages, 9 tables, under revie

Feline low-grade alimentary lymphoma: an emerging entity and a potential animal model for human disease

Background: Low-grade alimentary lymphoma (LGAL) is characterised by the infiltration of neoplastic T-lymphocytes, typically in the small intestine. The incidence of LGAL has increased over the last ten years and it is now the most frequent digestive neoplasia in cats and comprises 60 to 75% of gastrointestinal lymphoma cases. Given that LGAL shares common clinical, paraclinical and ultrasonographic features with inflammatory bowel diseases, establishing a diagnosis is challenging. A review was designed to summarise current knowledge of the pathogenesis, diagnosis, prognosis and treatment of feline LGAL. Electronic searches of PubMed and Science Direct were carried out without date or language restrictions. Results: A total of 176 peer-reviewed documents were identified and most of which were published in the last twenty years. 130 studies were found from the veterinary literature and 46 from the human medicine literature. Heterogeneity of study designs and outcome measures made meta-analysis inappropriate. The pathophysiology of feline LGAL still needs to be elucidated, not least the putative roles of infectious agents, environmental factors as well as genetic events. The most common therapeutic strategy is combination treatment with prednisolone and chlorambucil, and prolonged remission can often be achieved. Developments in immunohistochemical analysis and clonality testing have improved the confidence of clinicians in obtaining a correct diagnosis between LGAL and IBD. The condition shares similarities with some diseases in humans, especially human indolent T-cell lymphoproliferative disorder of the gastrointestinal tract. Conclusions: The pathophysiology of feline LGAL still needs to be elucidated and prospective studies as well as standardisation of therapeutic strategies are needed. A combination of conventional histopathology and immunohistochemistry remains the current gold-standard test, but clinicians should be cautious about reclassifying cats previously diagnosed with IBD to lymphoma on the basis of clonality testing. Importantly, feline LGAL could be considered to be a potential animal model for indolent digestive T-cell lymphoproliferative disorder, a rare condition in human medicine