Research Assistant in Quantitative Online Discourse Research

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Testo originale dell'annuncio (in inglese)

Research Assistant in Quantitative Online Discourse Research The Public Policy Group at ETH Zurich and the Public Discourse Foundation invite applications for a research assistant position starting as soon as possible and lasting one year, with the possibility of renewal. Project background You will be part of a collaborative team committed to rigorous research on how to improve public discourse on social and online media and other digital platforms. We study the effects of platforms’ policies and work with them to design and test interventions to improve the quality of online discussions and reduce harm caused by hate speech. To do so, we combine data from social media, online newspapers and original surveys with causal inference and machine learning methods to bring new evidence to bear on the urgent problems policymakers and practitioners face. We collaborate with a nonprofit dedicated to tackling hate speech, the Public Discourse Foundation , and various newspapers to translate our research into impact. Job description We are looking for a research assistant (with a workload of 20%) to join our ongoing research program on online discourse and how to improve it The primary responsibility lies with our data pipeline, which requires the review of any failed tests on our weekly data imports, as well as general maintenance and improvement of the code- and database This will take the form of responding to issues on GitHub, debugging issues in our R and Python scripts, creating pull requests, writing documentation, and collaboratively developing new features You will also analyse our data on online comments searching for interesting patterns or unexpected changes The general research program aims to understand online discourse, with a particular focus on the DACH region, and design and implement interventions to improve discourse and reduce hate speech We work together with online newspapers and use social media data Our research employs advanced statistical methods for causal inference and we develop state-of-the-art machine learning classifiers for both harmful and high-quality speech The position is located in the team of Dominik Hangartner at ETH Zurich, but you will also have the opportunity to work with an array of affiliated faculty as well as with the Public Discourse Foundation Profile Strong candidates will have most of the following: Completed undergraduate degree in a social science program with a preference for Political Science, Economics, Sociology, Data Science, Computational Social Science, or in a closely related discipline Knowledge of causal inference methods and/or machine learning Strong command of R (required) and/or Python (desirable) Familiarity with GitHub and collaborative work on GitHub Experience with Docker, SQL, and automated data pipelines desirable Ability to collaborate effectively with project team members and external stakeholders alike Proficiency and excellent writing skills in English; at least B1 German; basic French is an asset Knowledge of or interest in social media platforms and content moderation policies Interest in the societal applications of research We offer Highly collaborative work environment within a very motivated and supportive team Opportunity to develop a network with academics and practitioners Career mentoring by experienced researchers Salary in accordance with ETH guidelines Possibility to work remotely with flexible work hours (~10h/week, subject to fluctuating demand) Working, teaching and research at ETH Zurich We value diversity and sustainabilityIn line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value