Social media has become a key mechanism for the organization of grassroots movements. In the 2015 Barcelona City Council election, Barcelona en Comú, an emerging grassroots party, was the most voted one. This candidacy was devised by activists involved in the Spanish 15M movement in order to turn citizen outrage into political change. On the one hand, the 15M movement is based on a decentralized structure. On the other hand, political science literature postulates that parties historically develop oligarchical leadership structures. This tension motivates us to examine whether Barcelona en Comú preserved a decentralized structure or adopted a conventional centralized organization. In this article we propose a computational framework to analyze the Twitter networks of the parties that ran for this election by measuring their hierarchical structure, small-world phenomenon and coreness. The results of our assessment show that in Barcelona en Comu two well-defined ´ groups co-exist: a cluster dominated by the party leader and the collective accounts, and another cluster formed by the movement activists. While the former group is highly centralized like traditional parties, the latter one stands out for its decentralized, cohesive and resilient structure

1. Computational Framework for the
Assessment of New Forms of
Political Organization in Social Media
Pablo Aragón Asenjo
Máster en I.A. Avanzada
Universidad Nacional de Educación a Distancia
Supervisors
Andreas Kaltenbrunner
Luis Manuel Sarro Baro

2. Index
2Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
 Motivation
 Computational Framework
 Dataset
 Community detection
 Cluster characterization
 Conclusions and Future Work
 Dissemination

3. Motivation: Movement organizations
3Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Networked social movement: Networked in multiple forms (on/offline,
across platforms) without a central node, and with a decentered structure.
(Castells, 2013)
Change from logic of collective action to a logic of connective action.
(Bennett & Segerberg, 2013)

4. Motivation: Movement networks
4Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
“Decentralized structure,
based on coalitions of smaller
organizations”.
(González-Bailón et al, 2011)
“Decentralized organization,
without leaders or stable
representatives”.
(Aragón et al, 2015)
RT network of the 15M movement
May 15-22, 2011 (Aragón et al, 2015)

5. Motivation: Party organizations
5Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Iron Law of Oligarchy: Political parties, like any complex organization, self-
generate an elite (“Who says organization, says oligarchy”).
(Michels, 1915)
Elite theory: Small minorities (elites) hold the most power in political processes.
(Pareto et al, 1935; Mosca, 1939; Mills 1999)

6. Motivation: Party networks
6Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
In the Twitter party networks for
the 2011 Spanish election:
 Isolated clusters for each party.
 Minor/new parties were more
clustered and better connected.
 Every party cluster was strongly
centralized around candidate
and/or party profiles.
(Aragón et al, 2013)
RT network of political parties in
the 2011 Spanish election (Aragón et al, 2013)

7. Motivation: The 2015 Spanish local elections
7Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Grassroots parties emerged from the 15M movement:
 Barcelona en Comú
 Ahora Madrid
 Zaragoza en Común
 Marea Atlántica
 Compostela Aberta
 Por Cádiz Sí se puede
 Guanyem Badalona en Comú

8. Motivation: Research Question
8Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Assuming that:
 Barcelona en Comú emerged from the 15M
 the 15M movement followed a decentralized structure
Has Barcelona en Comú…
 preserved a decentralized structure?
 adopted a conventional centralized organization?

9. Computational Framework
9Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Community detection
Identify the organization of nodes in clusters: political party networks.
Cluster characterization
Characterize the topology of the intra-network of each cluster.

10. “Political parties share some interesting patterns of behavior, but also exhibit
some unique and interesting idiosyncrasies” (e.g. tagging practice of politicians)
(Lietz et al, 2015)
Sampling criteria based on
candidate and party
accounts:
 373 818 RTs
 RT network
 6 492 nodes
 16 775 edges
Dataset
10Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media

11. Community detection (I)
11Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
First result with the Louvain Method (Blondel et al, 2008):
 Eight major clusters (seven parties)
 Every cluster contains some media accounts: media build weak ties
 Analysis of the ego-network of relevant media accounts:
 Public TV account retweeted by users from every cluster
 Private media mostly retweeted by users from like-minded parties

12. Community detection (II)
12Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Every cluster contains some media accounts
Each execution produces different results:
Some media do not always belong to the same cluster
The real party intra-network structure is needed

13. Community detection (II)
13Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Every cluster contains some media accounts
Each execution produces different results:
Some media do not always belong to the same cluster
The real party intra-network structure is needed

14. Community detection (II)
14Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Every cluster contains some media accounts
Each execution produces different results:
Some media do not always belong to the same cluster
The real party intra-network structure is needed

15. Community detection (II)
15Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Every cluster contains some media accounts
Each execution produces different results:
Some media do not always belong to the same cluster
The real party intra-network structure is needed

16. Community detection (II)
16Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Every cluster contains some media accounts
Each execution produces different results:
Some media do not always belong to the same cluster
The real party intra-network structure is needed
Louvain Method with Confidence Interval
 Run multiple executions (N=100)
 Validate the stability of major clusters
 Just consider nodes that appear in the same cluster more than 1-ε (ε=0.05)

17. Community detection (III)
17Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Results with the Louvain Method
with Confidence Interval:
 Constant presence of eight major
clusters (seven parties) along the
100 executions.

18. Community detection (III)
18Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Results with the Louvain Method
with Confidence Interval:
 Constant presence of eight major
clusters (seven parties) along the
100 executions.
 Most media accounts do not
appear in major clusters

19. Community detection (III)
19Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Results with the Louvain Method
with Confidence Interval:
 Constant presence of eight major
clusters (seven parties) along the
100 executions.
 Most media accounts do not
appear in major clusters
 Two clusters for Barcelona
en Comú

20. Community detection (IV)
20Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Party
Movement

21. Community detection (V)
21Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Comparison to the
Clique Percolation Method
(Palla et al, 2005)
Similar results but…
 CPM is O(exp(n))
(NP-complete problem)
 CPM is not sensitive to different
sizes and structures of parties
 K-cliques are only the core of
the structure of party networks
(the periphery is relevant)

22. Cluster characterization
22Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Inspired by the social dimensions of García et al (2015):
 Hierarchical structure
 Small world
(Information efficiency)
 Coreness
(Social Resilience)

23. Cluster characterization: Hierarchical structure (I)
23Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Original In-degree centralization (Freeman, 1979)
Proposed Gini coefficient of the in-degree distribution

24. Cluster characterization: Hierarchical structure (II)
24Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Original In-degree centralization (Freeman, 1979)
Proposed Gini coefficient of the in-degree distribution

25. Cluster characterization: Small world (I)
25Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Original Average path length
Proposed Average path length + Clustering coefficient

26. Cluster characterization: Small world (II)
26Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Original Average path length
Proposed Average path length + Clustering coefficient

27. Cluster characterization: Coreness (I)
27Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Original Maximal k-core
Proposed Distribution of k-indices

28. Cluster characterization: Coreness (II)
28Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Original Maximal k-core
Proposed Distribution of k-indices

29. Conclusions (I)
29Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Contribution of the computational framework to the state-of-the-art:
 Community detection
The confidence interval identifies clusters in a more stable way
 Cluster characterization
New metrics better capture the social dimensions of clusters

30. Conclusions (II)
30Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
For Barcelona en Comú, two paradigms co-exist:
 A centralized and low resilient party cluster
 A decentralized and resilient movement cluster
Polarization like previous studies of election campaigns on Twitter
Data preparation process accentuated the polarization effect
Media accounts build weak ties between clusters
Public media became more plural than private media

31. Open questions and future work
31Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
How was the dual network structure of Barcelona en Comú built?
 As the confluence of minor parties and the 15M activists?
 As a party interface over a citizen decentralized system?
Is this dual paradigm observable in other grassroots parties?
Ahora Madrid? Zaragoza en Común? … Syriza?
Is this dual paradigm observable in other OSNs?
Facebook? Youtube? Instagram?

32. Dissemination: D-CENT project
32Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
This work has been funded by the
EU research project D-CENT
(FP7 CAPS 610349)
The results are contained in the
project deliverable “D2.3 - When a
movement becomes a party”

33. Dissemination: ICWSM-16
33Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
This research was accepted as a full
paper at the International Association
for the Advancement of Artificial
Intelligence Conference on Web and
Social Media (ICWSM-2016)
 Double-blind peer review process
 17% full paper acceptance rate

34. References (I)
34Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Aragón P., Congosto M., & Laniado D. (2014). Evolución del sistema- red 15m a través de
topología de redes. In Toret, J., Calleja, A., Marín, O., Aragón, P., Aguilera, M.,
Barandarian, X., Lumbreras, A. & Monterde, A. (2015). Tecnopolítica y 15M. La
potencia de las multitudes conectadas, Barcelona: Editorial UOC. ISBN: 978-84-9064-
458-4.
Aragón, P., Kappler, K. E., Kaltenbrunner, A., Laniado, D., and Volkovich, Y. (2013).
Communication dynamics in twitter during political campaigns: The case of the 2011
spanish national election. Policy & Internet, 5(2):183–206.
Bennett, W. L. and Segerberg, A. (2012). The logic of connective action: Digital media and
the personalization of contentious politics. Information, Communication & Society,
15(5):739–768.

35. References (II)
35Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., and Lefebvre, E. (2008). Fast unfolding of
communities in large networks. Journal of Statistical Mechanics: Theory and
Experiment, 2008(10):P10008.
Castells, M. (2013). Networks of outrage and hope: Social movements in the Internet age. J.
Wiley & Son
Freeman, L. C. (1979). Centrality in social networks conceptual clarification. Social
networks, 1(3), 215-239.
Garcia, D., Abisheva, A., Schweighofer, S., Serdult, U., and Schweitzer, F. (2015). Ideological
and temporal components of network polarization in online political participatory
media. Policy & Internet, 7(1):46–79.
González-Bailón, S., Borge-Holthoefer, J., Rivero, A., and Moreno, Y. (2011). The dynamics of
protest recruitment through an online network. Scientific reports.

36. References (III)
36Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media
Lietz, H., Wagner, C., Bleier, A., & Strohmaier, M. (2014). When Politicians Talk: Assessing
Online Conversational Practices of Political Parties on Twitter.
Michels, R. (1915). Political parties: A sociological study of the oligarchical tendencies of
modern democracy. Hearst’s International Library Company.
Mills, C. W. (1999). The power elite. Oxford University Press.
Mosca, G. (1939). The ruling class: elementi di scienza politica.
Palla, G., Derényi, I., Farkas, I., and Vicsek, T. (2005). Uncovering the overlapping community
structure of complex networks in nature and society. Nature, 435(7043):814– 818.
Pareto, V., Livingston, A., Bongiorno, A., Rogers, J. H., et al. (1935). Mind and society

37. Q & A
37Pablo Aragón Asenjo – Computational Framework for the Assessment of New Forms of Political Organization in Social Media