You’ve probably asked ChatGPT a question. You may even have used it to write a text for you. Artificial intelligence (AI) is pretty good at these things – so, what if we used it to answer survey questions, or help us summarize questionnaire responses? Researchers have started exploring whether AI …
In the first blog post of the KODAQS Toolbox series, we discussed how data quality issues can affect survey data. Similar challenges arise in digital behavioral data (DBD), though they often manifest differently. Researchers may encounter missing or deleted posts, inconsistent annotation schemes across datasets, or preprocessing decisions – such …
Chances are, you’ve run into this before. Regression results that change depending on how you handle missing values in your dependent variable. A long item battery where many respondents select the same response option all the way through. A set of survey items that do not seem to measure the …
Digital technologies have profoundly changed our lives. Social media, online platforms, and smartphones are a taken-for-granted part of our everyday life. They generate quantities of so-called Digital Behavioral Data, DBD — traces of human and algorithmic actions in the digital space. The problem is that DBD arise as a by-product …
Ob in der Politikberatung oder in der Sozialforschung: Wer auf Umfragedaten setzt, muss sicherstellen, dass diese auch wirklich verlässlich sind. Doch was tun, wenn sich in internationalen Großprojekten wie der European Values Study (EVS) oder dem International Social Survey Programme (ISSP) trotz hoher Standards Fehler in den Rohdaten befinden? Und …
In the course of datafication, social scientists are confronted with the increasing availability of digital behavioral data (DBD). Social media platforms, mobile apps, and sensors offer rich insights into human behavior, but these new data sources come with significant challenges in terms of quality. To address these issues, the two-day …