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

www.cyberemotions.eu

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 !

Negative stimuli

negative emotion forces ACTION

And they can be useful for fast reactions !!!

Collective effects do matter .... also for emotions !

Collective emotions

5.09.2012 Satellite meeting at ECCS'12

Emotion in cyberspace ?

8

Twitter Revolution

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

Collective emotions in cyber-communities ?

Pic. STOP SHREDDING OUR CONSTITUTION, USA 2012

SOCIAL MEDIA &US 2012 ELECTIONS

Collective Emotions in CyberspaceEuropean Union Research Project (FP7 FET)

Participant organisation name

Leaders Country Specialization

Warsaw University of Technology Janusz Hołyst Poland Physics of complex systems

EPF Lausanne Ronan Boulic Switzerland Virtual reality

University of Wolverhampton Michael Thelwall United Kingdom Webometrics

Österreichische Studiengesellschaft für Kybernetik

Robert Trappl Marcin Skowron

Austria Human-computer interactions

ETH Zürich Frank Schweitzer David Garcia

Switzerland Chair of systems design

Jozef Stefan Institute, Ljubljana Bosiljka Tadic Slovenia Physics of complex networks

Jacobs University, Bremen Arvid Kappas Germany Psychophysiology

Technical University Berlin Matthias Trier Germany Dynamic network analysis

Gemius SA Anna Winnicka Poland Online research agency

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€

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) .

CYBEREMOTIONS = data gathering + complex systems methods + ICT outputs

Main aims of Cyberemotions Project were

to understand the process of collective emotions formation in e-communities

http://sentistrength.wlv.ac.uk/Univ. Wolverhampton

WP3 created sentiment analysis softwareWP3 created sentiment analysis software- Used for research and for light displays- Used for research and for light displayson the London Eye during the Olympicson the London Eye during the Olympics

SentiStrengthSentiStrength

EMG(smiling, frowning)

EKG(heart rate)

EDA(sweating)

Continuous recording of psychophysiology during participation in a forum discussion

Data collected by Wolverhampton group

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.

Blog06crawl 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

4 million comments

Detection of collective emotions in cyber-communities

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).

Emotional clusters

Detection of collective emotions in cyber-communities

Emotional homophily of e-communities

neepneep )|()|(

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 t

Sentiment Triad Census Analysis Emotional persitence of IRC chatts

Emotional clustersEmotional avalanches

Hurst eponents

19

p(e|e)

Characteristic exponents α decay linearly with conditional probability of emergence of clusters of size two

2. Collective emotions in cyber-communities

)|(8.06.0 eep

Minority emotion (less frequent) posses larger value of α - the growth probability is more dependent on cluster size

Week interaction

Strong interaction

Rare emotions create stronger ties

20

Negative emotions as a fuel for discussion in cyber communities

Negative emotion Better not to be here …

A negative emotion results with escape response in real world

What about the Internet ?

21

|<e>| absolute value of the average emotion valence of the first 10 comments

<x>

Lenght of a thread 20 40 60 80

Number of comments in a thread

<e>

Average length of a thread as a function of the 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

Negative emotion as a fuel for discussions

WP6/JSI:Emotional Bots can induce collective mood

[Ref3]: B. Tadic and M. Suvakov , Arxiv:1305.2741 (2013)

joyBot polarizes network of Agents (red links indicate positive emotion messages), while miseryBot induces excess of negative emotion messages (carried by black links ) [Ref3]

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)

WP6/JSI: Agent-Based Model of Chats with Emotional Bots

Ref.: V. Gligorijevic, M. Suvakov and B. Tadic, DRAFT (2013)

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.]

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

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FAI

OFAI , Wien, Interactive Affective Bots

Environment[user] [web]

Perception

Natural LanguageUnderstanding

Affective Cues Sentiment classANEW: valence, arousal, dominanceLIWC: affective, ling.cognitive categories

Action categories, user_ID, channel_IDtimestamps

Control

Interaction Manager

Dialog Scripting

AIA Report. Module

Simulations

Collective Users Modelling

Individual User Modelling

Actuator-Communication Layer

WWWWWW• Tools for:• studying affective human-

computer 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

Contributor

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 Software1. Two H/W platforms: Desktop and CAVE2. Two S/W platforms: YaQ and Unity3D3. Pilot S/W OVS v1.1 accessible online Evaluation and

Validation

WP2 D2.4 Summary

Crowd Visualization with Emotion1.S/W platform: YaQ2.Number of virtual humans: 2003.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/fensPW/videos