RI/SES: Conference Proposal: Doctoral Consortium on Text as Data

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Computational methods from natural language processing enable new social science research that uses text as data; social science, in turn, offers insights that guide new applications of computation. However, opportunities for conversation and building collaboration among researchers in the computational and social sciences, especially students, are relatlively rare. The doctoral consortium that this award supports will bring together doctoral students working in computer science and those working in various areas of social science. Moreover, participating doctoral students are paired with faculty mentors in the complementary discipline, thus providing for each student a novel perspective that is likely to be both challenging and inspirational.The New Directions in Analyzing Text as Data (TADA) meeting has developed into a leading forum that brings these communities together, attracting top researchers from both sides. Holding a doctoral consortium at TADA 2018 initiates a new outreach effort to broaden participation at the meeting. By attending this doctoral consortium, computer science students benefit from the theoretical perspectives offered by social scientists, and social science students benefit by learning about new computational methods to support their research involving text data. Funding is used primarily to support students to attend and fully participate in the meeting, where they are given an opportunity to present their current work and receive individual mentoring. Mentors are recruited from the ranks of TADA veteran attendees. These mentorship pairings are expected to significantly impact the direction of ongoing doctoral research, bringing natural language processing and social science closer together and creating a community with diverse young leaders who can fluently communicate across the disciplines.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.