Indeed, computational analysis is opening new possibilities for exploring challenging questions at the heart of some of the most pressing contemporary cultural and social issues. (2017) used this opportunity to combine rich online data with computational methods to study a current question: Does eliminating these “echo chambers” diminish the amount of hate speech overall? Exciting opportunities like these, at the intersection of “thick” cultural and societal questions on the one hand, and the computational analysis of rich textual data on larger-than-human scales on the other, are becoming increasingly common. In June 2015, the operators of the online discussion site Reddit banned several communities under new anti-harassment rules. Interdisciplinary insights and partnerships are essential for realizing the full potential of any computational text analysis involving social and cultural concepts, and the more we bridge these divides, the more fruitful we believe our work will be. This leads to our final goal: to help promote interdisciplinary collaborations. Still, given our diversity of disciplinary backgrounds and research practices, we hope to capture a range of ideas and identify commonalities that resonate for many. Our guidance is based on our own experiences and is therefore inherently imperfect. Second, we hope to provide a set of key questions that can guide work in this area. First, we aim to shed light on thorny issues not always at the forefront of discussions about computational text analysis methods. In this article we describe our experiences with computational text analysis involving rich social and cultural concepts.
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