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Islamophobia, a negative predilection towards the Muslim community, is present on social media platforms. In addition to causing harm to victims, it also hurts the reputation of social media platforms that claim to provide a safe online environment for all users. The volume of social media content is impossible to be manually reviewed, thus, it is important to find automated solutions to combat hate speech on social media platforms. Machine learning approaches have been used in the literature as a way to automate hate speech detection. In this paper, we use deep learning techniques to detect Islamophobia over Reddit and topic modeling to analyze the content and reveal topics from comments identified as Islamophobic. Some topics we identified include the Islamic dress code, religious practices, marriage, and politics. To detect Islamophobia, we used deep learning models. The highest performance was achieved with BERTbase+CNN, with an F1-Score of 0.92.