Computational Social Science to Gauge Online Extremism

Tracking #: 486-1466


Emilio FerraraORCID logo

Responsible editor: 

Tobias Kuhn

Submission Type: 

Research Paper


Recent terrorist attacks carried out on behalf of ISIS on American and European soil by lone wolf attackers or sleeper cells remind us of the importance of understanding the dynamics of radicalization mediated by social media communication channels. In this paper, we shed light on the social media activity of a group of twenty-five thousand users whose association with ISIS online radical propaganda has been manually verified. By using a computational tool known as dynamical activity-connectivity maps, based on network and temporal activity patterns, we investigate the dynamics of social influence within ISIS supporters. We finally quantify the effectiveness of ISIS propaganda by determining the adoption of extremist content in the general population and draw a parallel between radical propaganda and epidemics spreading, highlighting that information broadcasters and influential ISIS supporters generate highly-infectious cascades of information contagion. Our findings will help generate effective countermeasures to combat the group and other forms of online extremism.



  • Reviewed

Data repository URLs: 


Date of Submission: 

Monday, January 30, 2017

Date of Decision: 

Friday, February 10, 2017

Nanopublication URLs:



Solicited Reviews:


Paper Withdrawn by Author

This paper was withdrawn by the author on 10 February 2017.

Meta-Review by Editor

The following is the meta-review from 10 February 2017 before the paper was withdrawn by the author:

Thank you for your submission to Data Science. I inform you that the acceptance or rejection of your manuscript is still UNDECIDED (we don't use "major revisions" or "minor revisions"). I ask you to respond to the enclosed comments by the reviewers, and to take them into account for your revised version.

In particular, the following problems identified by the reviewers need to be addressed:

- Data availability: Your work does currently not follow our data availability requirements (see the paragraph on "Data" in the author guidelines:
- The problem of Research Question 1, as noted by Reviewer 2 ("not actually a real research question")
- Lacking discussion of implications, as noted by Reviewer 2
- Problems with the contagion part of the analysis, as noted by Reviewer 3
- Potential problems with the plots, as noted by Reviewer 3

Below I also list some very minor comments and typos from my side.

Please provide point-by-point responses to the issues raised by the reviewers, and prepare a separate text file that contains these responses. The revised version of the paper is expected within 20 days.

Typos and minor comments from my side (I might be wrong about some of the typos though):

- "1.2 million of these tweets was" > "... were"
- "The plot also introduce" > "... introduces"
- "We note how the connectivity growth dimension spans three orders of magnitude [...] This
means that some users’ followerships grows tens of times faster than the rate at which
they follow others": Shouldn't it be (at least) "hundreds of times faster"?
- I would be helpful if Figure 4 had labels for what the x and y axes stand for, instead of just "x" and "y".
- "significantly less tweets" > "... fewer ..."
- "similar amounts of retweets than broadcasters": not sure how to correctly phrase this but "similar ... than" sounds wrong to me
- "does not appear set of" > "does not appear in the set of"

Tobias Kuhn (