In this workshop, we discuss the design and implementation of virtual reality (VR) visualizations of network data (such as co-author networks, flight connections between cities, and social networks). We introduce participants to network science concepts and discuss Lateral Thinking Gone VR, a narrative VR visualization that we will use to explore a communication network that represents German-speaking Telegram groups and channels between April 2020 and December 2021. We will implement exploratory interactions for interlinked 3D network graph visualization and geospatial map of Germany.
This workshop is informed by information and library science, network science, and political science (while covering analysis and cutting-edge visualization of social media data), and is thus relevant for informetric and scientometric theories and their deployment.
The visualization of complex social network data does not only aid data analysis for researchers but is key to the effective communication of scientific findings to the wider public. Virtual reality provides effective and immersive tools for data-driven storytelling in support of translation of scientific findings to the public. VR environments encourage the co-exploration of data visualizations and embedding data in sophisticated, visually rich environments, while being accessible to anyone that can use a VR headset.
Note that you do not need to bring a VR headset for this workshop! We have six Meta Quests 2 available.
This workshop has three goals:
- Set up a virtual 3D room with a network visualization
- Utilize native functionalities of the Unity platform (https://unity.com) to ingest data points and bind them to 3D objects in a fully interactive, 3D environment
- Implement a details on demand interaction using state-of-the-art VR controllers
The public discourse accompanying major political and social events is heavily facilitated by social media platforms. While companies like Twitter and Facebook enforce restrictions on anonymity of their users, smaller, less moderated platforms, such as Telegram, allow their users to post, comment, and otherwise interact with content in relative anonymity. Recently, the COVID-19 pandemic led to an upheaval surrounding public health measurements, school closures, and vaccination requirements. The (semi-)public discourse that ensued was facilitated, in part, by Telegram. Lateral Thinking Gone VR, the VR research project underlying this workshop, is presented in three vignettes: a directed 3D network of channels and groups showing cross-references between entities and their weight; a geospatial layout mapping entities to their physical location on top of a 3D map of the German-speaking part of Europe; and a geospatial and topical map that demonstrates the push and pull between geospatial and topical proximity that dissolves or intensifies connections between groups and channels. The goal of Lateral Thinking Gone VR is threefold: (1) to understand the growth of the movement (i.e., how it grew over time, how it started in a few small cities and spread, etc.); (2) to understand different relationships of importance (i.e., the frequency with which certain sources are cited in comparison to others); and (3) to visualize the relationship between topical and geospatial proximity, i.e., whether groups are more frequently connected via cross-references if they are from the same city or if they cover similar topics. In this workshop, we discuss the hardware and software setup for Lateral Thinking Gone VR while giving an introduction to the interactions afforded to the user as well as the data handling to be done when visualizing data in 3D VR.
You can read more about the ongoing research on Telegram by one of the organizers of this workshop here.
What We Will Build in the Workshop
Free University of Berlin and Weizenbaum Institute for the Networked Society, Berlin, Germany
We would like to thank:
- Naval Pandey
- Devon Scoles
- Yash Shah
- Purnima Surve
Research Lead, Cyberinfrastructure for Network Science (CNS) Center.
Luddy School of Informatics, Computing, and Engineering