Since 2020, our group has been a meeting point for researchers at different career stages and with various backgrounds who share a common interest in the applications of data and computational social science in three interconnected areas: data mining, econometric modelling, and machine learning and artificial intelligence.
Our mission is to foster collaboration and the exchange of ideas in computational social science to foster research and disseminate specific knowledge and techniques to wider audiences. Our commitment to open science leads us to promote transparency and open access to our data, results, and processes in order to generate effective solutions to current challenges and foster a positive impact on society.
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Since its creation in 2020, Training Data Lab has served as a meeting point for researchers at different stages of their careers interested in applied social sciences and quantitative methods. In these five years, we have promoted different collaborations and projects such as, for example, the Ranking Chileno de Ciencia Política (CPS-Ranking). We also launched the series of working papers Tufte Working Papers (ISSN 2735-6043).
Since December 2019, our team has enthusiastically maintained the Chilean Political Science Ranking (CPS-Ranking), a quarterly assessment highlighting the scholarly impact of political scientists in Chile and those focused on Chilean topics through the measurement of their H-index based on Google Scholar profiles. Over five years, this initiative grew notably, starting modestly with 125 profiles and reaching 206 in our final edition in December 2024. This growth reflected genuine interest and recognition within the Chilean political science community, with scholars voluntarily joining or being recommended by their peers. We are deeply grateful for this engagement and the widespread support from researchers nationwide.
