Due to lack of consensus on what constitutes hate speech and the challenges in operationalizing existing definitions at the scale of current online platforms, prior work has used a mix of manual and automated term selection strategies to identify terms that are likely to occur in hateful texts [@chandrasekharan2018you; @davidson2017automated]. While focusing on speech targeting Muslims and Islam, we similarly combine existing lexicons with terms obtained through a combination of manual and automated steps (§\[subsec:query-construction\]).

Data Collection {#sec:data}
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Our goal is to characterize and measure online hate speech targeting Muslims and Islam in reaction to major Islamist terror attacks and Islamophobic attacks perpetrated in Western countries. Here, we describe our data collection process, which attempts to be inclusive (high-recall) and hence uses a broad definition of hate and counter-hate speech. We iteratively expand an initial query of keywords related to relevant items by identifying new keywords in the retrieved messages. Our base datasets contain messages from Twitter and Reddit, and a collection of news articles; these are not associated to any particular event, but cover messages potentially related to hate and counter-hate speech over a period of 19 months: from January 1, 2016 to August 1, 2017.

Data Sources 