id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_7ihigjw62fbpbeeprwp224cgna	Pete Burnap	Us and them: identifying cyber hate on Twitter across multiple protected characteristics	2016	15	.pdf	application/pdf	9054	991	62	developing a blended model that incorporates knowledge of how different protected characteristics (e.g. race and sexuality) intersect in cyber hate speech. In this study, the aim was to build cyber hate speech classifiers for text that is targeted towards individuals or social groups based on their race, sexual orientation or disability. effectiveness of identifying othering terms and their success as features in a machine classifier for cyber hate targeted at specific religious groups, the present research aimed to The key finding from previous research was that the inclusion of typed dependencies in the classification of religious cyber hate reduced the false negative rate by % when compared to using typed dependencies as features in the classification of cyber hate reduced false positive rate Furthermore, we built a data-driven blended model of cyber hate to improve classification where more than one protected characteristic may be attacked (e.g. race and sexual	./cache/work_7ihigjw62fbpbeeprwp224cgna.pdf	./txt/work_7ihigjw62fbpbeeprwp224cgna.txt