Online behaviour may appear coordinated either through coincidence or deliberate action, overt or covert. Recent events have shown that covert coordinated activity can shift online opinion dramatically. We devised a method to identify sets of accounts whose behaviour appears coordinated in different ways, based on network and temporal information sourced from social media, and tested it against two relevant datasets. To improve our approach, we reviewed a range of literature to identify new coordination patterns and non-network methods to apply. As a result, we have concluded that coordination varies by domain, may differ from coincidental behaviour only by degree or may require content analysis to identify. Future work will therefore move towards content-based analysis. Poster presented at the Australian Social Network Analysis Conference, 27-29 November 2019, Adelaide, South Australia.

1. Coordination StrategiesAbstractAbstract
Gang-Up
Coordination
Detection
Pipeline
Example Communities
ReferencesReferences
Results
International Influence Propaganda Radical Social Movements
Self-Organisation
ConclusionConclusion
On Coordinated Online Behaviour
Derek Weber1,2
derek.weber@adelaide.edu.au
1University of Adelaide, School of Computer Science
2Defence Science and Technology Group, Department of Defence
Amplify by Repost
Post Repost
time
Heavily reposting content to make it
appear popular by gaming platform
trending algorithms (Keller et al., 2017)
Channel Pollution
Flooding a community united by a
hashtag, page or forum with repeated
or objectionable content, causing the
platform operator to shut it down as
spam (Nasim et al., 2018)
Groups of accounts harassing other
individual accounts or a community
(Kumar et al., 2018)
5.4.3.2.1.
Highly coordinating political accounts in DS2
(1440 min. window, coloured by degree of activity)
timetime
HostileHostile
FriendlyFriendlytime
Hostile
Friendly
Good Post Junk Post
time
Channel: e.g., #OurPartyRocks
t0
t1
t2
time
t1
t2
t3
Australian Social Network Analysis Conference (ASNAC) – 27-29 November 2019
Coordination Theory (CSCW)
Nature
Flocking occurs to improve
foraging, protection, migration,
and aggression. Coordination of
movement is achieved through
‘interaction rules’, monitoring
neighbours’ speed and direction,
resulting in directional and
spatial organisation
(Herbert-Read, 2016).
Stigmergy is the coordination of
agents via traces left in the
environment, which leaves
agents disconnected and even
unaware of each other
(Marsh & Onof, 2008).
Artificial
Boids have been used to mimic
natural flocks by giving simple
movement rules to autonomous
agents. (Reynolds, 1987).
Radical social movements rely on clear messaging
(low noise) but need to encourage freedom of
expression.
Application of neuroscience ‘fractal scaling’ to
Twitter discussions of 15M groups in Netherlands
and Spain revealed types of noise, which related to
the stability of groups: ‘Pink’ noise permitted stable
groups which adapted as the environment changed,
unlike ‘brown’ and ‘white’ noise, which formed non-
resilient groups or no groups, respectively.
(Swann & Ghelfi, 2019)
Influence Operations
4 Ds of Disinformation:
Dismiss, Distort,
Distract, Dismay
(Nimmo, 2015)
Steps in Influence Operations:
Manufacturing consent
Then: Control of mass media through vested
interests (Herman & Chomsky, 1988)
Now: Democratisation of propaganda via
automation in social media; “megaphone effect”;
normalisation of fringe voices
(Woolley & Guilbeault, 2018)
• Find cracks in society
• Build audiences
• Distort narratives
• Use kernels of truth
• Conceal truth
• Cultivate ‘useful idiots’
as proxies
• Deny, deny, deny
• Play the long game
(Schneier, 2019)
J.E. Herbert-Read. Understanding how animal groups achieve coordinated movement. Journal of Experimental Biology,
219(19):2971–2983, 2016.
F.B. Keller, D. Schoch, S. Stier, and J.-H. Yang. How to manipulate social media: Analyzing political astroturfing using ground
truth data from South Korea. ICWSM, pp. 564–567, 2017.
S. Kumar, W.L. Hamilton, J. Leskovec, and D. Jurafsky. Community interaction and conflict on the web. WWW, pp. 933–943,
2018.
T.W. Malone and K. Crowston. The interdisciplinary study of coordination. ACM Computing Surveys, 26(1):87–119, 1994.
L. Marsh and C. Onof. Stigmergic epistemology, stigmergic cognition. Cognitive Systems Research, 9(1-2):136–149, 2008.
M. Nasim, A. Nguyen, N. Lothian, R. Cope, and L. Mitchell. Real-time detection of content polluters in partially observable
Twitter networks. WWW (Companion Volume), pages 1331–1339, 2018.
B. Nimmo. Anatomy of an info-war: How Russia’s propaganda machine works, and how to counter it —
StopFake. https://www.stopfake.org/en/anatomy-of-an-info-war-how-russia-s-propaganda-machine-works-and-how-to-
counter-it/, May 2015. (Accessed on 2019-10-16).
C.H. Builder, S.C. Bankes, and R. Nordin. Command concepts: A theory derived from the practice of Command and Control.
Monograph Report MR-775-OSD, RAND Corporation, 1999.
C.W. Reynolds. Flocks, herds and schools: A distributed behavioral model. SIGGRAPH, pp. 25–34. ACM, 1987.
B. Schneier. 8 Ways to Stay Ahead of Influence Operations — Foreign Policy. https://foreignpolicy.com/2019/08/12/8-
ways-to-stay-ahead-of-influence-operations/, August 2019. (Accessed on 2019-10-24).
D. Spry. Facebook diplomacy: A data-driven, user-focused approach to Facebook use by diplomatic missions. Media
International Australia, 168(1):62–80, June 2018.
Thomas Swann and Andrea Ghelfi. Pink organising: Notes on communication, self-organisation, noise and radical social
movements. Organization, 26(5):696–715, 2019.
D.C. Weber and F. Neumann. Detecting Coordinated Behaviour in Social Media Using Streaming Graphs. AAAI’20, submitted.
S.C. Woolley and D.R. Guilbeault. Computational Propaganda in the United States of America: Manufacturing Consensus
Online. Oxford, UK: Project on Computational Propaganda, Working Paper No. 2017.5, 2017.
http://weeklyworldnews.com/
1. Real-world patterns of coordination are highly
domain-specific.
2. Patterns may differ from typical behavioural
patterns only by degree.
3. Coordination may only be apparent through
examination of content.
4. Content analysis may be required to reveal the
intention of observed coordination.
Online Coordination: A network of connections
among online accounts, potentially with a temporal
aspect, informed through the accounts’ behaviour
and content, not necessarily via direct connections.
Two datasets
γ=15 γ=60 γ=360 γ=1440
DS1 0.87 0.85 0.86 0.88
DS2 0.92 0.73 0.38 0.92
Top F1 scores of three unary classifiers.
(γ is window size in minutes.)
DS1: 56k tweets extracted from Twitter IRA release, Nov. 2016
DS2: 120k tweets from a local election, early 2018
Amplify by Repost HCCs were found in
both datasets, forming star shapes.
Unary classifiers trained on political HCCs
(right) found other HCCs were similar.
• Both military and diplomatic missions rely on
centralised hierarchical command structures. Both
use high level plans to achieve operational goals.
• Autonomy on the ground may be required to adapt
and take advantage of local conditions.
• Command concepts are communicated within the
command and control system (Builder et al., 1999).
• Local diplomatic requirements may not match
government-level requirements, which can affect
local social media engagement (Spry, 2018).
“Coordination is managing
dependencies between activities”
Processes achieving coordination manage: shared
resources; producer/consumer relationships;
simultaneity constraints; and task/subtask constraints.
(Malone & Crowston, 1994)
https://www.flickr.com/photos/amagill/5605231677
Online behaviour may appear coordinated either
through coincidence or deliberate action, overt
or covert. Recent events have shown that covert
coordinated activity can shift online opinion
dramatically.
We devised a method to identify sets of accounts
whose behaviour appears coordinated in
different ways, based on network and temporal
information sourced from social media, and
tested it against two relevant datasets.
To improve our approach, we reviewed a range
of literature to identify new coordination
patterns and non-network methods to apply.
As a result, we have concluded that coordination
varies by domain, may differ from coincidental
behaviour only by degree or may require content
analysis to identify. Future work will therefore
move towards content-based analysis.
http://wikipedia.org/
(Weber & Neumann, submitted)