Ecological approaches toHuman Collective Behavior

Javier Borge-Holthoefer - @CoSIN3_UOC

Barcelona, 2016V Jornada Complexitat.cat

Preliminaries

Nestedness Modularity

spectral method (largest eigenvalue )

NODF (Paired Overlap – Decreasing Fill)

Many heuristics –EO, spectral, greedy…

Olesen, Bascompte, Dupont, Jordano. The modularity of pollination networks. PNAS 104(50) 2007

Barber’s bipartite networks Q

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“Studying mesoscale network structure goes very far beyond studying community structure” (Mason Porter)http://www.slideshare.net/masonporter/mesoscale-structures-in-networks-62116874

Antecedents

Bustos et al. The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems. PLoS One 7(11) (2012)

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Antecedents

Garas, Rozenblat and Schweitzer. The network structure of city-firms network. http://arxiv.org/abs/1512.02859 (2015)

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Consensus emergenceCooperation and Competition

Context

Meme (hashtag) aspects

Growth and survival

Evolution and mutation

Leskovec, Backstrom, Kleinberg. Meme-tracking and theDynamics of News cycle. Proc. 15th SIGKDD, 497-506 2009

Temporal dynamics modeling

Where are the users?

User aspects

Structural properties

Bursty behavior

Information cascades

Where are the memes?Barabási. The origin of bursts and heavy tails in humandynamics. Nature 435 2005

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Bipartite approach

From information systems…

Typically focused on one side

Users or memes (hashtags)

… to information ecosystems

Users and memes (hashtags)

Rich collection of interactions

Bipartite representation

Users compete for visibility

Memes compete for attention

Gonçalves et al. Validation of Dunbar’snumber in Twitter conversations. PLoSOne 6(8), 2011

Weng et al. Competition among memes ina world with limited attention. Sci Rep 2,2012

(mutualistic setting?)

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Álvarez-Baños et al. The role of hidden influentials in the diffusion of online informationcascades. EPJ Data Science 2(6) 2013

Bipartite temporal approach

Alarcón et al. Year-to-year variation in the topology of a plant-pollinator interaction network. Oikos 117(12) 2008

Diaz-Castelazo et al. Changes of a mutualistic network over time. Ecology 91(3) 2010

Olesen, Bascompte, Elberling, Jordano. Temporal dynamics in a pollinator network. Ecology 89(6) 2008

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Data representation

Time-resolved data

w-day sliding window scheme

Window advances w each stepδ

For each snapshot

collect N most active users

collect their M correspondinghashtags

build an N x M binary matrix

Caveat: this implies that users andhashtags may enter/exit the systemeach time step

http://arxiv.org/abs/1501.068099

Consensus build-up: 15M

Modularity Q optimization

nestedness evaluation

Fortunato. Community detection ingraphs. Phys Rep 3 2010

Staniczenko, Kopp, Allesina. The ghost ofnestedness in ecological networks. Nat. Comm. 4 2012

Bell et al. Graphs for which the least eigenvalueis minimal. Linear Algebra Appl. 429 2008

http://arxiv.org/abs/1501.0680910

Socio-message: segreggation-to-coordination cross-over

Almost perfect anti-correlation

Socio-message is intuitive… but, why?

hashtags

users

Bastolla, et al. The architecture of mutualisticnetworks minimizes competition and increasesbiodiversity. Nature 458 2009

Growing term intraguild competition term Mutualistic term

Nestedness minimizes competition

Nestedness facilitates coexistence ofindividuals

Competitive interactions favourcompartmentalised structures

Thebault, Fontaine. Stability of ecologicalcommunities and the architecture of mutualisticand trophic networks. Science 329 2010

(…) negative interactions increase,mutualism decreases

Odum. Trends expected in stressed ecosystems.BioScience 35 1985

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Socio-message is intuitive… but, why?

modular nested

diedielivelive

dielivedielive http://arxiv.org/abs/1501.06809

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Consensus emergenceCooperation and Competition

(in the city)

Data

The problem grows…

221021,Coffee Shop,40.748939,-73.99228,New York,US

49932,Department Store,40.664266,-73.720107,New York,US

209256,Gym,40.732322,-73.985359,New York,US

15235,Home (private),40.716162,-73.88307,New York,US

198359,Office,40.755881,-73.985778,New York,US

90903,Medical Center,40.745104,-73.982484,New York,US

66378,Food Truck,40.739535,-73.990817,New York,US

82300,Miscellaneous Shop,40.833007,-74.009933,New York,US

3510,Grocery Store,40.690095,-73.955077,New York,US

23164,Coffee Shop,40.751591,-73.974121,New York,US

(460 cities)

(alternative datasets: Instagram, Flickr, credit card transactions)

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From urban systems…

Typically focused on one side

Citizens or services or locations

… to urban ecosystems

Citizens and services and locations

Rich collection of interactions

Multilayer-bipartite representation

Citizens compete for resources

Services compete for benefit

(mutualistic setting?)

asia

n re

stau

rant

coffe

e

colle

ge

gas stat

ion

cine

ma

Urban Ecosystem approach

What do locations compete for?

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services

use

rs

Chennai (China)

Urban Ecosystem

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Three-way nestednessand/or modularity

Urban Ecosystem: open fronts

Network growth model

Methodological issues

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servicescells

citizens

1972

1987

1992

2001

2014

Doha (Qatar)

Growth and Morphology

Urban Ecosystem: open fronts

Implications for system robustnessand resilience (to what?)

Implications for systemchanges(extinctions, invasions)

Cooperation and competition

The modular-nested dichotomy

Mono- vs. multi-centric?

Innovative vs. service oriented?

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Javier Borge-Holthoefer - @CoSIN3_UOC

Barcelona, 2016

www.jbh.cat