| 54344 |
Creator |
b040f63fe07909831fea669121318768 |
| 54344 |
Creator |
b8d521a6173aa941c32cd5686f640bfa |
| 54344 |
Creator |
b74f948be6ce6303fceb26df2557739a |
| 54344 |
Date |
2018-05-27 |
| 54344 |
Is Part Of |
repository |
| 54344 |
abstract |
In an increasingly digital world, identifying signs of online extremism sits at the
top of the priority list for counter-extremist agencies. Researchers and governments
are investing in the creation of advanced information technologies to identify and
counter extremism through intelligent large-scale analysis of online data. However,
to the best of our knowledge, these technologies are neither based on, nor do they
take advantage of, the existing theories and studies of radicalisation. In this paper
we propose a computational approach for detecting and predicting the radicalisation
influence a user is exposed to, grounded on the notion of ’roots of radicalisation’
from social science models. This approach has been applied to analyse and compare
the radicalisation level of 112 pro-ISIS vs.112 “general" Twitter users. Our results
show the effectiveness of our proposed algorithms in detecting and predicting radicalisation
influence, obtaining up to 0.9 F-1 measure for detection and between 0.7 and 0.8 precision
for prediction. While this is an initial attempt towards the effective combination
of social and computational perspectives, more work is needed to bridge these disciplines,
and to build on their strengths to target the problem of online radicalisation. |
| 54344 |
authorList |
authors |
| 54344 |
presentedAt |
ext-9052638d70faca087ff4e2fb3525e9ad |
| 54344 |
status |
peerReviewed |
| 54344 |
uri |
http://data.open.ac.uk/oro/document/646132 |
| 54344 |
uri |
http://data.open.ac.uk/oro/document/646134 |
| 54344 |
uri |
http://data.open.ac.uk/oro/document/646135 |
| 54344 |
uri |
http://data.open.ac.uk/oro/document/646136 |
| 54344 |
uri |
http://data.open.ac.uk/oro/document/646137 |
| 54344 |
uri |
http://data.open.ac.uk/oro/document/646138 |
| 54344 |
uri |
http://data.open.ac.uk/oro/document/659822 |
| 54344 |
type |
AcademicArticle |
| 54344 |
type |
Article |
| 54344 |
label |
Fernandez, Miriam ; Asif, Moizzah and Alani, Harith (2018). Understanding the Roots
of Radicalisation on Twitter. In: In WebSci ’18: 10th ACM Conference on Web Science,
27-30 May 2018, Amsterdam, Netherlands, ACM (Association for Computing Machinery). |
| 54344 |
label |
Fernandez, Miriam ; Asif, Moizzah and Alani, Harith (2018). Understanding the
Roots of Radicalisation on Twitter. In: In WebSci ’18: 10th ACM Conference on Web
Science, 27-30 May 2018, Amsterdam, Netherlands, ACM (Association for Computing Machinery).
|
| 54344 |
Publisher |
ext-3f0dbda1e05ba2f7a6d5604466f5f27c |
| 54344 |
Title |
Understanding the Roots of Radicalisation on Twitter |
| 54344 |
in dataset |
oro |