Public event

Data Science Brown Bag: Towards understanding socio-semantic configurations in networks

Join us for a talk by Lena Mangold on a how to integrate metadata to enhance our understanding of social network dynamics and structures.

Abstract from the speaker: 

When analysing social networks, it is often helpful to consider attributes that are known about the actors, i.e. metadata, to provide further insights into the underlying network dynamics. For example, when considering online public discourse represented by an interaction network of social media users we might not only be interested in the links between the user nodes, but also in additional user information, such as demographics or political preference, and the interplay between such user categories and link formation. One way in which we can integrate metadata in network analysis is to explore the relationship between metadata and what we call the network’s block structure — a division of the network into groups of nodes that are similar in terms of how they are connected to each other and the rest of the network. In the network science literature, the prevalent assumption of an intrinsic connection between metadata and block structure has faced scrutiny in recent years. Nevertheless, a tool for measuring the metadata-structure relationship for the purpose of systematic comparative meta analyses has been notably lacking.

About the speaker: 

Lena Mangold is a PhD researcher in the Computational Social Science Team lead by Camille Roth, at Centre Marc Bloch (Berlin). In the context of the ERC socsemics project, her research focuses on the mathematical description and categorisation of socio-semantic clusters in online public spaces: subgroups of users not only segregated from the wider conversation in terms of social interaction but also separated from (and less exposed to) opinions and content outside of their group. 

Bring your own lunch bag! Light pastries and drinks will be available in case you forget to bring it. 

The Data Science Brown Bag Series is an informal and interactive gathering where participants bring their own brown bag lunch and engage in discussions on research and insights the field of data and computational social science (light pastries and drinks will be available if you forget your lunch bag!). 

The series provides a platform for data enthusiasts, researchers, and practitioners to share their experiences, best practices, and emerging methodologies and research in using data science to analyze and understand social and political phenomena. The brown bag talk series is for anyone interested in data science and social science to network, learn, and share ideas in a casual and friendly setting.

Contact person

  • William Lowe, Senior Research Scientist
  • Huy Ngoc Dang, Manager of Data Science Lab & Programme Coordinator of Master of Data Science for Public Policy