Klaus Ackermann

I am currently a Researcher and Data Scientist at the Center for Data Science and Public Policy at the University of Chicago. I hold a PhD  in Economics from Monash University, Australia. Contact: ackermann@uchicago.edu

Research Philosophy
My passion is in technology, economics, data and computational approaches to get exciting insights about human behaviour. Broadly speaking, my research sits under the headline: how does technological progress affect societies and vice versa? What behavioural patterns that were disguised previously can now be researched as people reveal their choices through the use of technology? How can we use collected data to improve operational outcomes of not for profit organizations by using Machine Learning ? There are social issues that need to be addressed on an individual level, but I believe it is possible to impact the world on an aggregate level by using data.

Recent projects

The Internet as Quantitative Social Science Platform: Insights from a Trillion Observations

Abstract: With the large-scale penetration of the internet, for the first time, humanity has become linked by a single, open, communications platform. Harnessing this fact, we report insights arising from a unified internet activity and location dataset of an unparalleled scope and accuracy drawn from over a trillion (1.5$\times 10^{12}$) observations of end-user internet connections, with temporal resolution of just 15min over 2006-2012. We first apply this dataset to the expansion of the internet itself over 1,647 urban agglomerations globally. We find that unique IP per capita counts reach saturation at approximately one IP per three people, and take, on average, 16.1 years to achieve; eclipsing the estimated 100- and 60- year saturation times for steam-power and electrification respectively. Next, we use intra-diurnal internet activity features to up-scale traditional over-night sleep observations, producing the first global estimate of over-night sleep duration in 645 cities over 7 years. We find statistically significant variation between continental, national and regional sleep durations including some evidence of global sleep duration convergence. Finally, we estimate the relationship between internet concentration and economic outcomes in 411 OECD regions and find that the internet's expansion is associated with negative or positive productivity gains, depending strongly on sectoral considerations. To our knowledge, our study is the first of its kind to use online/offline activity of the entire internet to infer social science insights, demonstrating the unparalleled potential of the internet as a social data-science platform.

Available on arXiv

Limiting the market for information as a tool of governance: Evidence from Russia

Abstract: This paper presents a novel measure of subtle government intervention in the news market achieved by throttling the Internet. In countries where the news media is highly regulated and censored, the free distribution of information (including audio and any visual imagery) over the Internet is often seen as a threat to the legitimacy of the ruling regime. This study compares electoral outcomes at polling station level between the Russian presidential election at the beginning of March 2012 with the parliamentary election held three months earlier in December 2011. Electoral regions in two cases are compared: regions that experienced internet censorship at the presidential election but not the parliamentary election; versus regions that maintained a good internet connection without interference for both elections. Internet censorship is identified using randomised internet probing data in accuracies down to 15-minute intervals for up to a year before the election. Using a difference in difference design, an average effect of increased vote share of 3.2 percentage point for the government candidate is found due to internet throttling. Results are robust to different specifications and electoral controls are used to account for the possibility of vote rigging.

Working Paper

Designing Policy Recommendations to Reduce Home Abandonment in Mexico

Designing Policy Recommendations to Reduce Home Abandonment in Mexico

Ackermann, K., Blancas Reyes, E., He, S., Anderson Keller, T., van der Boor, P., Khan, R., Ghani, R. and González, J.C., 2016, August. Designing Policy Recommendations to Reduce Home Abandonment in Mexico. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 13-20). ACM.

Link to the paper.

A resource efficient big data analysis method for the social sciences: the case of global IP activity

This paper presents a novel and efficient way of analysing big datasets used in social science research. We provide and demonstrate a way to deal with such datasets without the need for high performance distributed computational facilities. Using an Internet census dataset and with the help of freely available tools and programming libraries, we visualize global IP activity in a spatial and time dimension. We observe a considerable reduction in storage size of our dataset coupled with a faster processing time.

Ackermann, K. and Angus, S.D., 2014. A resource efficient big data analysis method for the social sciences: the case of global IP activity. Procedia Computer Science, 29, pp.2360-2369.

Link to the paper.


I have written a postgres database extension that allows a query to be executed in parallel and therefore speed up the process time. The code can be found on GitHub.