Download - Interaction on the web
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Interaction on the web
Vera Menezes (UFMG/CNPq/FAPEMIG)
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Complexity / Ecology
In this presentation, I will talk about interaction on the web from the perspective of complex systems and ecology science.
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Complexity
“The study of the phenomena which emerge from a collection of interacting objects.” (Johnson, 2007:3-4)
“Complexity is synonymous with the study of agents and networks together.” (Johnson, 2007:13)
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Ecology
• “Ecology is the science of relationships between living organisms and their environment. Human ecology is about relationships between people and their environment.” (Marten 2001:1)
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Complexity / Ecology
Human interaction has complexified with the emergence of web technologies and the creation of a virtual ecological community constituted exclusively by language.
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The discursive community on the web is an ecological dynamic system that shares some common interests. The system is open, non-linear and subject to attractors.
Complexity
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Dynamic: the discursive community is never the same. It changes all the time.
Open: high frequency of new members and new technologies coming into the system all the time.
Dynamic and open
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Non-linear: “the emergent behavior is often non-linear, meaning disproportional to its causal factors.” (Larsen-Freeman & Cameron 2008:2)
Butterfly effect (e.g. Virals)
Hipertextual, non-chronological order.Number of participants may increase and then the rate may slow down. Eg.: Orkut
Non-linear
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The concept of attractor
•“States or particular modes of behaviors that the system prefers”. (Thelen and Smith 1994: 56).
•An attractor is a region of a system’s state space into which the system tends to move. (Larsen-Freeman & Cameron 2008:50)
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“The horse-and-rider behavior is stable for a while. As its speed increases,it will eventually move into a new attractor, for example, from ‘trot’ to ‘canter’.” (Larsen-Freeman & Cameron 2008:50)
Example of attractor
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Some attractors in social Networks
If we analyze social networks such as Facebook and Twitter we will find out some relative stable interacting behaviors.
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Some attractors in social Networks
• Sharing texts, videos, jokes, photographs.
• Arguing.• Philosophizing.• Self-helping. • Description of daily routines.• Invitations to (game) apps.• Complaints.• Jesus-loves-you advising.
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Some attractors in social Networks
• Political engagement/analysis. • Football praising and teasing..• TV reviewer.• Announcements (e.g. shows).• Requests (e.g. blood
donation).• Protests.• Indirect messages.• Bullying.
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Ecological Perspective
We live in ecological communities made up of physical and virtual biomes.
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Ecological Perspective
Species in a biome interact in different ways. mutualism commensalism competition predation.
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Ecological Perspective
Our interactions metaphorically reproduce the behaviors of the species in natural environments and can be understood in the light of those concepts.
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Ecological Perspective
Mutualism
All participants benefit from the interaction.e.g. Sharing relevant information on Twitter or Facebook.
Wiki collaboration
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Ecological Perspective
Commensalism:
Some participants benefit, others remain unaffected. e.g.: description of daily routine in Facebook and Twitter; telling the time; Indirect messages.
Lurkers on educational forums.
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Ecological Perspective
Competition
Everybody
is affected negatively.
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Competition
“Twitter is no longer playing quite so nicely with other competitors in the social networking sandbox.
After recently prohibiting the users of LinkedIn from posting tweets directly to their profiles on that network, San Francisco-based Twitter just cut off users of the Instagram photo-sharing service in a similar manner.”Available at: <http://www.sfexaminer.com/local/2012/07/competition-increases-among-social-networking-firms>
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Ecological Perspective
Predation
One benefits and the others are disavantaged
e.g. mockering,
cyber bullying.
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Conclusion
But why do different forms of interaction fit together so well?
Discursive complex systems organize themselves by means of processes similar to natural selection in biological evolution.
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Conclusion
• As technologies evolve more complex communities emerge on the web. Some of them stop to evolve and eventually die.
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Conclusion
• My hypothesis is that ubiquitous, multitask and multimedia communities will have more chances to survive.