Author: Evgeniia Krichever
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Beyond personal data: a new initiative to support early-career researchers with hard-to-share data
This project tackles bottlenecks in sharing sensitive research data in the social sciences and humanities. A key feature of this initiative is a series of three in-person workshops, designed to give researchers the tools and insights needed to share sensitive data responsibly.
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Computational Social Science: Ethics and Conceptual Transparency
The way researchers define and operationalize key terms such as fairness, bias, and privacy doesn’t just affect research outcomes—it fundamentally shapes the societal impacts of CSS, making this ethical consideration critical.
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Benchmarking in Social Science: The Case of the Data Challenge for Predicting Fertility in the Netherlands (PreFer)
Fertility outcomes, or the number and timing of children, influence numerous aspects of individual lives and the development of societies. While researchers have extensively studied how specific factors – such as age, socioeconomic status, or network characteristics – affect fertility, relatively little attention has been paid to the predictability of fertility outcomes. How accurately can…
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ODISSEI Portal from Prototype to Production
We are happy to announce a new release of the ODISSEI Portal. Find more than 9,000 social sciences datasets available across different Dutch data providers. With the new release metadata is continuously updated so that the Portal provides an up-to-date discovery platform for social sciences data in the Netherlands. We have also included a new…
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Practical tips on sharing code
In this short article, we review some tips and best practices to share code, as a complement to the ODISSEI lecture on the ODISSEI Code Library (see slides). The short article is meant to help ODISSEI users to comply with the User Policy, but it also provides general tips and resources that can also be…
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Benchmarking
A benchmarking challenge is when various teams of participants are set a challenge to predict a particular outcome. At the end of the challenge, the teams’ performances are evaluated based on a predefined set of matrices and evaluation criteria.
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The ODISSEI Media Content Analysis Lab: improving access to media content data
The MCAL team built the MCALentory, a searchable inventory of publications on media content analysis published in various communication science journals since 2001.
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Linking Historical Records and Contemporary Administrative Data
As part of ODISSEI, data from the HSNDB dataset Historical Sample of the Netherlands (HSN) has been linked with the current Statistics Netherlands microdata and catalogued in the ODISSEI Portal. This enables links between the historical research conducted using the HSN and contemporary society and the outcomes studied by social scientists, whilst simultaneously allowing social…
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Publishing, evaluating and understanding Network Embeddings
NetAudit bridges the gap between social and computer scientists by developing tools to analyse large population networks through interpretable network embeddings.
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Data donation research in practice: How are Students Using Generative AI for Their Studies?
This blog post describes a study led by Dr. Karin van Es and Dr. Dennis Nguyen at Utrecht University, which investigates how students are using generative AI tools like ChatGPT for academic purposes. A key innovation in this study is the use of data donation—a method where students voluntarily share their ChatGPT conversation data. Using…