[Air-L] What Makes an Online Community? Social Media Workshop with Prof Axel Bruns

[Olga Boichak]

Please join us for the 2021 Social Media Workshop: '*What Makes an Online
Community?*' featuring a plenary by AoIR Past President Professor Axel
Bruns (Queensland University of Technology) and a series of lightning talks
by University of Sydney researchers: Prof. Eduardo Altmann, Ms Venessa
Paech, Dr. Aim Sinpeng, Dr. Olga Boichak, and Dr. Tristram Alexander.


The event will be held virtually via Zoom, join via the link below:

*When: Tuesday, November 30th 10:00am AEDT *(Monday, November 29th 6:00pm
EST)

What time is it for me?
<https://www.timeanddate.com/worldclock/fixedtime.html?msg=What+Makes+an+Online+Community%3F+Social+Media+Workshop+with+Prof+Axel+Bruns&iso=20211130T10&p1=240&ah=2>

Where: https://uni-sydney.zoom.us/j/88452302048



*Plenary: Online Communities and Where to Find Them: Conceptual and
Analytical Frameworks (Prof. Axel Bruns, QUT)*Groups, communities, crowds,
audiences, publics: the terms we use to describe groupings of online
participants are varied, and differ from field to field: the ‘communities’
detected by network mapping algorithms might not qualify as communities
from a media and cultural studies perspective, for example. This talk
distinguishes some of the key terms used in describing online groupings,
and outlines the analytical frameworks that may be used to distinguish
them.


*Speaker Biographies *

*Axel Bruns *is an Australian Research Council Laureate Fellow and
Professor in the Digital Media Research Centre at Queensland University of
Technology in Brisbane, Australia, and a Chief Investigator in the ARC
Centre of Excellence for Automated Decision-Making and Society. His books
include Are Filter Bubbles Real? (2019) and Gatewatching and News Curation:
Journalism, Social Media, and the Public Sphere (2018), and the edited
collections Digitizing Democracy (2019), the Routledge Companion to Social
Media and Politics (2016), and Twitter and Society (2014). His current work
focusses on the study of user participation in social media spaces, and its
implications for our understanding of the contemporary public sphere,
drawing especially on innovative new methods for analysing 'big social
data'.


*Eduardo Altmann *is a Professor in Mathematics at the University of
Sydney. He is a mathematician/physicist with expertise in the dynamics of
natural language, including the use of automated text classification
methods and information theoretic measures for classifying text similarity.
He, along with co-workers, developed stochastic block model methods for
network and text analysis.


*Venessa Paech *is an internationally regarded online community expert and
educator and a PhD Candidate studying the intersection of AI and online
communities at the University of Sydney. She co-founded Australian
Community Managers (ACM), the national centre for training and resources.
Venessa has developed and teaches the first post-graduate online community
management Unit for the University of Sydney.


*Olga Boichak *is a Lecturer in Digital Cultures at the University of
Sydney, Department of Media and Communications. She has a track record of
publications on digital war, legitimising state power, transnational
mobilisation, and algorithmic surveillance, and her research interests span
networks, narratives, and cultures of activism in the digital age.


*Aim Sinpeng *is a Senior Lecturer in the Department of Government and
International Relations at the University of Sydney. She is the author
of *Opposing
Democracy in the Digital Age: The Yellow Shirts in Thailand *(University of
Michigan Press, 2021) and co-editor of *From Grassroots Activism to
Disinformation: Social Media in Southeast Asia *(ISEAS, 2020).


*Tristram Alexander *is a Senior Lecturer in Physics at the University of
Sydney. He is a physicist with expertise in the modelling of nonlinear
dynamical systems with many interacting elements, including social media
dynamics. He has developed a suite of processing tools to identify and
analyse communities in Twitter stream data.