Marta Kołczyńska

Sociology • Social Science Data & Methods

What comes first: Exploring public interest in tech-related topics

What comes first? Wikipedia, Google, News Interest in technology Cross-correlations News coverage versus Wikipedia page views with Maria Khachatryan, Filip Kowalski, Jakub Siwiec, and Paweł Zawadzki The Hackathon Next Generation Internet Data Sprint was organized by the Digital Economy Lab of the University of Warsaw on November 9 and 10, 2018. The goal of the hackathon was to explore datasets on Wikipedia page views and edits, Reddit posts, media mentions, and others, to generate insights about the use of the internet and new technologies.

Biking in Barcelona: Green City Hackathon

BigSurv18 and the Green City Hackathon Team number 5 Data Bike use Altitude of Bicing stations Location of mechanical and electric bike stations Empty stations by station altitude Next steps with Saleha Habibullah, Sakinat Folorunso, and Vera Paul BigSurv18 and the Green City Hackathon One of accompanying events of the BigSurv18: Big Data Meets Survey Science conference in Barcelona last week was the Green City Hackathon.

Political participation patterns in Poland

Political participation in Poland Latent class analysis Three types of participants: the Disengaged, Activists, and Protesters Region maps I recently came across Jennifer Oser’s 2017 article in Social Indicators Research about “political tool kits”, i.e. profiles (or patterns) of participation in different political activities. Her general argument is that research on citizen participation would benefit from analyses of such participation patterns instead of (or at least in addition to) just looking at determinants of participation in single activities.

Personal vs. household income in cross-national surveys

Sample correlations Sample correlations by gender Sample correlations by age Sample correlations by education Contrast Conclusion One of the reasons for the harmonization of personal income in addition to household income was to check if the two correlate highly enough to use household income as a substitute for personal income in analyses where economic status is a control variable. This would be great, because household income variables are available in 1177 surveys out of 1721 analyzed in the Survey Data Recycling dataset (SDR) version 1, while personal income only in 453 surveys.

Harmonizing measures of income in cross-national surveys

Data Number of response options Item non-response Distributions Harmonized target variables Next steps with Przemek Powałko Individual economic status is a necessary element of almost all sociological analyses, including studies of political attitudes and behavior. To supplement the already harmonized variables in the Survey Data Recycling dataset (SDR) version 1 and for the purposes of my resesarch of the effects of education on political engagement, Przemek and I harmonized two additional variables: personal income and household income1.

Measuring the level and inequality of political participation with survey data

Political participation in the ESS Country levels of political participation Inequality of political participation Democracy indicators Economic inequality Matrix scatter plots How to measure political inequality? The Variaties of Democracy project (V-Dem) has a set of political equality indicators that capture the extent to which political power is distributed according to wealth and income, membership in a particular social group, gender or sexual orientation (cf. V-Dem Codebook v.

Age distributions in samples from cross-national survey projects

Cross-national survey projects conduct surveys on representative samples of adult populations. How do the distributions of respondents’ age vary across surveys carried out in the same country in different years and different projects? Like in a couple of previous posts (here, here and here) I use data from the Survey Data Recycling dataset (SDR) version 1, which includes selected harmonized variables from 22 cross-national survey projects. SDR only includes surveys that claim to have samples representative for adult populations.

Reliability of survey estimates: Participation in demonstrations

Data Differences within country-years Differences by groups Gender Age Urban/rural residence Education Sampling scheme The growth in cross-national survey projects in the last decades leads to situations when two or more surveys are carried out in the same country and the same year but in different projects, and contain overlapping sets of survey questions. Assuming that the surveys are based on representative samples - a claim that major cross-national survey projects typically make - it could be expected that estimates from surveys carried out in the same country and year are reasonably close.

tidytext analysis of TED talks

Setup tidy TED talks Applause, LOL Sentiment This year I spent two weeks of the summer attending the Summer Institute for Computational Social Science Parter Site (SICSS) in Tvärminne and Helsinki, Finland, organized by Matti Nelimarkka from Aalto University and the University of Helsinki, assisted by two TAs: Juho Pääkkönen and Pihla Toivanen from the University of Helsinki. I highly recommend it to anyone with background in the social sciences and interested in computer and data sciences, or the other way around!

Validating survey data: Educational attainment in SDR and the OECD

Educational attainment data OECD data SDR data Cleaning and merging SDR and OECD data Results The curious case of ISSP Switzerland Conclusion Appendix with Przemek Powałko General population surveys with representative samples should have a similar education structure as shown by data from administrative sources, especially if survey weights are used. In this post we compare sample aggregates from 15 cross-national survey projects (including the European Social Survey, the World Values Survey and the European Values Study, and others) from the Survey Data Recycling database with educational attainment statistics from the OECD.