Marilena Hohmann

Hi! I'm Marilena, a PhD student in Social Data Science at the University of Copenhagen. My PhD research, advised by Roberta Sinatra, examines the social organization of scientific and political communities. I am interested in how social groups are shaped by shared ideas, preferences, and practices. Currently, I'm working on an exciting project investigating the impact of generative AI on the scientific ecosystem. Before starting my PhD, I obtained an MSc in Social Data Science (University of Copenhagen, 2022) and a BA in Media and Communication Studies (Freie Universität Berlin, 2020).

As part of my PhD, I visited the research groups of Aaron Clauset and Dan Larremore at the University of Colorado Boulder during the spring term 2024. I had a great time exploring the research environment at CU and, of course, enjoying the beautiful mountains nearby!

Publications

Quantifying ideological polarization on a network using generalized Euclidean distance
Marilena Hohmann, Karel Devriendt, Michele Coscia
Science Advances, 2023

Paper
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Presentations

Estimating affective polarization on a social network

Marilena Hohmann

9th International Conference on Computational Social Science (IC2S2), Copenhagen, July 2023

Quantifying ideological polarization on a network using generalized Euclidean distance

Marilena Hohmann

International School and Conference on Network Science (NetSci), Vienna, July 2023

Estimating affective polarization on a social network

Marilena Hohmann

The International Conference on Complex Networks and their Applications, Palermo, November 2022

Who cares about Brüssel? Bedeutung transnationaler Interessenvertretung bei europäischen Medienunternehmen und -verbänden

Marilena Hohmann

Annual conference of Netzwerk Medienstrukturen, Leipzig, October 2018

Teaching

I have been a teaching assistant for the courses listed below.

Social Data Science Base Camp

University of Copenhagen (2022)

Mandatory first-year course (15 ECTS) of the MSc in Social Data Science. The course offers an in-depth introduction to data analysis in Python, including basic principles of programming, data collection via scraping and APIs, data wrangling, visualization, and regression analyses.

Python Tsunami

University of Copenhagen (2020-2022)

3-day course for researchers at the Faculty of Health and Medical Sciences, organized by the Center for Health Data Science. The course introduces data structures in Python, iterables, conditional and flow control statements, pandas, and visualization.

Intro to Academic Writing

Freie Universität Berlin (2019-2020)

Mandatory first-year course of the BA in Media and Communication Studies. The course covers the basics of academic writing, including literature databases, references, and argumentation, reading, and writing strategies.