CAMsterdam at SemEval-2019 task 6: Neural and graph-based feature extraction for the identification of offensive tweets

We describe the CAMsterdam team entry to the SemEval-2019 Shared Task 6 on offen-sive language identification in Twitter data.Our proposed model learns to extract tex-tual features using a multi-layer recurrent net-work, and then performs text classification us-ing gradient-boosted decision trees (GBDT). A self-attention architecture enables the model to focus on the most relevant areas in the text.We additionally learn globally optimised em-beddings for hashtags using node2vec, which are given as additional tweet features to the GBDT classifier.Our best model obtains78.79% macro F1-score on detecting offensive language (subtask A), 66.32% on categorising offence types (targeted/untargeted; subtask B),and 55.36% on identifying the target of of-fence (subtask C)

The Early Royal Society and Visual Culture

Recent studies have fruitfully examined the intersection between early modern science and visual culture by elucidating the functions of images in shaping and disseminating scientific knowledge. Given its rich archival sources, it is possible to extend this line of research in the case of the Royal Society to an examination of attitudes towards images as artefacts –manufactured objects worth commissioning, collecting and studying. Drawing on existing scholarship and material from the Royal Society Archives, I discuss Fellows’ interests in prints, drawings, varnishes, colorants, images made out of unusual materials, and methods of identifying the painter from a painting. Knowledge of production processes of images was important to members of the Royal Society, not only as connoisseurs and collectors, but also as those interested in a Baconian mastery of material processes, including a “history of trades”. Their antiquarian interests led to discussion of painters’ styles, and they gradually developed a visual memorial to an institution through portraits and other visual records.AH/M001938/1 (AHRC