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Online network organization of Barcelona en Comú, an emergent movement-party

Overview of attention for article published in Computational Social Networks, September 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)

Mentioned by

twitter
36 X users

Readers on

mendeley
20 Mendeley
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Title
Online network organization of Barcelona en Comú, an emergent movement-party
Published in
Computational Social Networks, September 2017
DOI 10.1186/s40649-017-0044-4
Pubmed ID
Authors

Pablo Aragón, Helena Gallego, David Laniado, Yana Volkovich, Andreas Kaltenbrunner

Abstract

The emerging grassroots party Barcelona en Comú won the 2015 Barcelona City Council election. This candidacy was devised by activists involved in the Spanish 15M movement to transform citizen outrage into political change. On the one hand, the 15M movement was based on a decentralized structure. On the other hand, political science literature postulates that parties develop oligarchical leadership structures. This tension motivates to examine whether Barcelona en Comú preserved a decentralized structure or adopted a conventional centralized organization. In this study we develop a computational methodology to characterize the online network organization of every party in the election campaign on Twitter. Results on the network of retweets reveal that, while traditional parties are organized in a single cluster, for Barcelona en Comú two well-defined groups co-exist: a centralized cluster led by the candidate and party accounts, and a decentralized cluster with the movement activists. Furthermore, results on the network of replies also shows a dual structure: a cluster around the candidate receiving the largest attention from other parties, and another with the movement activists exhibiting a higher predisposition to dialogue with other parties.

X Demographics

X Demographics

The data shown below were collected from the profiles of 36 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 25%
Student > Master 4 20%
Researcher 3 15%
Student > Doctoral Student 2 10%
Professor 1 5%
Other 3 15%
Unknown 2 10%
Readers by discipline Count As %
Social Sciences 13 65%
Computer Science 2 10%
Unspecified 1 5%
Physics and Astronomy 1 5%
Engineering 1 5%
Other 0 0%
Unknown 2 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 26. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 February 2021.
All research outputs
#1,493,185
of 25,732,188 outputs
Outputs from Computational Social Networks
#1
of 41 outputs
Outputs of similar age
#28,800
of 326,453 outputs
Outputs of similar age from Computational Social Networks
#1
of 3 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 41 research outputs from this source. They receive a mean Attention Score of 3.8. This one scored the same or higher as 40 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,453 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them