www.cyberemotions.eu
Collective Emotions in Cyberspace
Short review of Cyberemotions project results
In the name of CYBEREMOTIONS Consortium
Janusz Hołyst, Project Coordinator, Warsaw University of Technology,
jholyst@if.pw.edu.pl
Plan
• Emotions, cyberemotions, collective emotions
and collective cyberemotions
• Cyberemotions Project structure
• Main results of various Project layers:
- data collection and classification
- collective character of cyberemotions
and data driven models of cybercommunities
- project ICT outputs
There is no agreement what emotions
are but they are important for our life !
And they can be useful
for fast reactions !!!
Negative stimuli
negative emotion
forces ACTION
Collective effects do matter .... also for emotions !
Collective emotions
Emotion in cyberspace ?
5.09.2012 Satellite meeting at ECCS'12
Collective emotions in cyber-communities ?
Twitter
Revolution
SOCIAL MEDIA &
US 2012 ELECTIONS
Pic. STOP SHREDDING OUR CONSTITUTION, USA 2012
Pic. Arab Spring in Egypt 2011
congratulations Egypt the
criminal has left the palace
– a tweet from Egyptian
protest leader Wael Ghonim.
Twitter can help organize. Facebook can
help get the word out. YouTube provides
evidence. Over the past few years, we've
seen that social media can be a powerful
tool in assisting revolutions in countries.
- Cheryl Aguilar, EthnoBlog
8
Collective Emotions in Cyberspace
European Union Research Project (FP7 FET)
Large-scale integrating project, ICT Call 3 Science of Complex Systems for Socially
Intelligent ICT. Duration: 1 Feb. 2009 - 31. Jan. 2013. EC funding 3.6 M€
Participant organisation
name
Leaders
Country
Specialization
Warsaw University of Technology
EPF Lausanne
Janusz Hołyst
Ronan Boulic
Poland
Switzerland
Physics of complex systems
Virtual reality
University of Wolverhampton
Österreichische Studiengesellschaft
für Kybernetik
ETH Zürich
Michael Thelwall
Robert Trappl
Marcin Skowron
Frank Schweitzer
David Garcia
Bosiljka Tadic
Arvid Kappas
Matthias Trier
Anna Winnicka
United Kingdom
Austria
Webometrics
Human-computer interactions
Switzerland
Chair of systems design
Slovenia
Germany
Germany
Poland
Physics of complex networks
Psychophysiology
Dynamic network analysis
Online research agency
Jozef Stefan Institute, Ljubljana
Jacobs University, Bremen
Technical University Berlin
Gemius SA
Main aims of Cyberemotions Project were
to understand the process of collective emotions
formation in e-communities
CYBEREMOTIONS = data gathering + complex systems methods + ICT outputs
Expected impact of CYBEREMOTIONS
• new classes of realistic models of emotionally reacting E-users
• new kind of intelligent self-adapting programs, cyber-tutors,
cyber-advisors for e-communities (long time scale)
• to create theoretical background for the development of the next
generation emotionally-intelligent ICT services using universal
methods of complex systems (long time scale) .
Univ. Wolverhampton
http://sentistrength.wlv.ac.uk/
SentiStrength
WP3 created sentiment analysis software
- Used for research and for light displays
on the London Eye during the Olympics
Continuous recording of psychophysiology during participation in a forum discussion
EMG
(smiling, frowning)
EKG
(heart rate)
EDA
(sweating)
Data collected by Wolverhampton group
4 million comments
BBC Forum BBC “Religion and Ethics” and “World / UK News” message boards starting
from the launch of the website (July 2005 and June 2005 respectively) until the beginning of the
crawl (June 2009).
#comments
2,474,781
#users 18,045
# threads97,946
Digg The analysis spans the months February to April 2009 and consists of all the stories,
comments and users that contributed to the site during this period. The resulting dataset
contains approximately
1.9 million stories, 1.6 million comments and 800 thousand users.
Blog06
crawl of approximately 100,000 blogs and which spans 11 weeks, from 06/12/2005 to
21/02/2006", i.e. the dataset contains webpages from 100,000 different blogs (more than 3
million webpages) . The blogs are from all over the world, although there is an emphasis on
English content
#comments 242,057
#discussions 1219
Detection of collective emotions in cyber-communities
Emotional clusters
Emotions (emotional valence e ={ +1,0,-1})
We define an emotional cluster of size n as a chain of n consecutive messages with
similar sentiment orientations (i.e. negative, positive or neutral).
Detection of collective emotions in cyber-communities
Emotional homophily of e-communities

p(e | ne)  p(e | e)n
The presence of a longer
cluster of coherent
emotional expressions
increases a possibility to
follow the cluster by a
comment with the same
emotion.
Conditional probability for cluster growth increases as a power-law with cluster
length.
Collective emotions of cybercommunities detected by various
methods
Emotional avalanches
t
Emotional clusters
Emotional persitence of IRC chatts
Hurst eponents
Sentiment Triad Census Analysis
2. Collective emotions in cyber-communities
Characteristic exponents α
decay linearly with
conditional probability of
emergence of clusters of size
two
  0.6  0.8 p(e | e)
Strong
interaction
p(e|e)
Rare emotions create
stronger ties
Week
interaction
Minority emotion (less
frequent) posses larger
value of α - the growth
probability is more
dependent on cluster size
19
Negative emotions as a fuel for discussion in
cyber communities
A negative emotion results with escape response in real
world
Negative emotion
Better not to be here …
What about the Internet ?
20
Negative emotion as a fuel for discussions
Lenght of a thread 20 40 60 80
<e>
Number of comments in a thread
Average length of a thread as a function of
the absolute value of the average emotion
valence of the first 10 comments
<x>
|<e>| absolute value of the average emotion
valence of the first 10 comments
Emotional beginnings of the threads, whether positive or negative,
usually lead to longer discussions
21
WP6/JSI:Emotional Bots can induce
collective mood
Simulations revealed how
Agents collective
emotion
polarizes under the influence
of positive/negative emotion
Bots [Fig.]
Bot's impact on Agents can
be measured; It relies on the
network
structure
(which
propagates emotion among
Agents) and on the
self-organized nature of the
dynamics (which enhances
correlations)
joyBot polarizes network of Agents (red links indicate
positive emotion messages), while miseryBot induces
excess of negative emotion messages (carried by black
links ) [Ref3]
[Ref3]: B. Tadic and M. Suvakov , Arxiv:1305.2741 (2013)
WP6/JSI: Agent-Based Model of Chats
with Emotional Bots
Agent-Based Model with
emotional Agents +
Moderators + Bots developed
& validated
Agents designed with certain
'human' attributes (inferred from
the empirical data )
Experimental emotional Bot
used as input: response of
Agents simulated
Experimental data: Users group according to their
similarity in emotional communications with Bot (5
communities, left);
More cohesive groups appear when they are placed in
an interactive environment (simulated, right) [Ref.]
Ref.: V. Gligorijevic, M. Suvakov and B. Tadic, DRAFT (2013)
Austrian Research Institute for Artificial Intelligence – OFAI
OFAI , Wien, Interactive Affective Bots
• Tools for:
• studying affective humancomputer interactions:
- single user, -multiple users
• acquisition of data on users'
sentiment towards entities,
events, processes
• experimental evaluation of
theoretical models
•
•
•
•
•
Example realizations of IAB:
Affect Listener Dialog Participant
Affective Interaction Analyser
Affective Supporter and Content
Environment
[user]
[web]
WWW
Actuator-Communication Layer
Perception
Natural Language
Understanding
Control
Interaction Manager
Dialog Scripting
Affective Cues
Sentiment class
ANEW: valence,
arousal, dominance
LIWC: affective, ling.
cognitive categories
Action categories,
user_ID, channel_ID
timestamps
AIA Report. Module
Simulations
Collective Users
Modelling
Individual User
Modelling
OFAI, Vienna,Affect Listener
- Development of Affective Dialog Systems
• Evaluation of systems in 5
experimental setups
• Dialog system vs. Wizard of OZ
• dialog realism, chatting
enjoyment, emotional connection
• Effect of system’s affective profile
• positive, negative, neutral
• Effect of interaction context and
roles assigned to the user and
system
• Effect of fine grained communication scenarios
• social sharing of emotions, getting acquainted with someone
• Attention and social interactions context - social exclusion
Jacobs University: Social Exclusion by the
Conversational System?
***
Mean subjective evaluation of attention
paid by the bartender. *** significant
difference at p < .0001 .
EPFL: emotions in virtual reality
Crowd Visualization Software
1. Two H/W platforms: Desktop and CAVE
2. Two S/W platforms: YaQ and Unity3D
3. Pilot S/W OVS v1.1 accessible online
WP2
D2.4 Summary
Evaluation and
Validation
Crowd Visualization with Emotion
1. S/W platform: YaQ
2. Number of virtual humans: 200
3. Display rate: more than 60 fps
Sentiment network visualisation (TU
Berlin)
Positive
subnetwork
Selected project achievements
•
Emotional responses can be predicted from observation of sentiment
fluctuations in physiological and Twitter data.
•
Asymmetry is crucial for emotion animations in facial expressions.
•
Sentistrength program used during Olympic Games to monitor daily
moods in UK (display at London Eye).
•
Developed affective bots are capable to communicate with humans.
• Emotions can be crucial for leaving of Open Source Community by their
active members (including project leaders).
• Chat Bots developed for data driven models of e-communities can
propagate negative/positive emotions and polarize channel moods.
•
Chat Bots can lead to social exclusion of e-community members.
• Universal tools developed for automatic analysis and visualisation of
emotion propagation in social data.
Conclusions
.
• We demonstrated that collective emotions do exist
in a broad class of e-communities
• Collective emotional dynamics is vital for the
efficiency and survival of e-communities
• The current technology makes possible to create
bots that can influence human emotions
• Understanding the role of and strategic use of
cyberemotions will be crucial for the future society
because of technological, economical and political
issues.
More results will be presented
at next presentations, posters
and www.cyberemotions.eu
CyberEmotions video lectures:
https://www.youtube.com/user/fen
sPW/videos