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Interactive Map of Islamophobia (By Gender)

Each color-coded dot on this map represents an incident or event that reflects Islamophobic attitudes, ranging from instances of harassment and vandalism to national political speech and elections. As you will see in the legend, the events are color-coded according to the gender of the victim(s). We have included “Transgender” in our coding scheme even though we have no data points in which a transgender Muslim is identified as an individual victim of a hate crime or bias related incident. We made the decision to do so because we surmise that just as in other instances in which transgender people are victims of hateful acts and are afraid to come forward as trans (or at all), there is a good possibility that there are transgender Muslims who are suffering in silence.

We would also like to emphasize that incidents/events targeting Muslim women often go unreported as well. On the basis of substantial anecdotal data, it is likely that these hate crimes or bias-related incidents occur on a daily basis and in many different settings, especially for those who wear any kind of headscarf or other covering. These everyday incidents/events are not reflected in our data because they are often not reported to law enforcement or civil right organizations.

Click on individual dots to reveal a short description of the event and a source for additional reading. Each pop-up box also indicates the year because this map includes all items from the dataset. It may be easier to click on individual events/incidents if you use the zoom function, which will also enable you to differentiate data points in crowded areas. You can “grab” the map to move around the country by left clicking your mouse and holding it down. You can view a single layer of incidents/events by using the click box in the upper left-hand corner of the screen.

The map includes complete (if not exhaustive) data for 2014, 2015, 2016, and 2017 (with regular updates) as well as partial data for 2011-2013. We also have a map of Islamophobic events and incidents as they accumulate over time, showing when and where spikes of activity occur, an interactive map layered by year, and an interactive map layered by type of incident.