Project description
Detecting violent online radicalisation with text mining
In the face of increasing numbers of terrorist attacks carried out by individuals radicalised via terrorist propaganda on the internet, social media providers lack an adequate tool to identify online terrorist-related content. They currently rely on proprietary spam-fighting tools, user reports and human analysis to track radicalised accounts. To address this issue, Insikt Intelligence developed a social data mining platform called INSIKT to detect violent online radicalisation. The EU-funded INSIKT project aims to improve and integrate the platform with tools to help law enforcement agencies identify radical content, suspicious messages and covert radicalisation, all through sophisticated text-mining algorithms.
Objective
In 2015-2016, 20+ terrorist attacks occurred in EU28, all of them carried out by individuals radicalized by terrorist propaganda. Recruitment of this new breed of terrorists was done via social media and the Internet.
To prevent such events from happening in the future and fight radicalization, it is crucial to detect cyberpropaganda early. However, social media providers (e.g. Twitter) admit that at the moment there is no adequate tool to identify terrorist-related content on the Internet. As the result, they are forced to rely on proprietary spam-fighting tools, user reports and human analysis to track down radicalized accounts that promote terrorism.
Insikt Intelligence is a Spanish SME led by the EYIF 2016 Female Web Entrepreneur finalist that developed INSIKT, a novel social data mining platform to detect & defeat violent online radicalization. An early version of INSIKT was validated by several EU law enforcement agencies (LEAs), approved and attracted commercial interest. This Phase 2 project will trial INSIKT at 4 European LEAs that are looking for effective tools to prevent radical messages from spreading and reaching people vulnerable to radicalization.
INSIKT provides a novel solution for LEA analysts to detect terrorist propaganda on all social media: it identifies radical content, suspicious messages and covert radicalization process with the help of sophisticated text mining algorithms. INSIKT relies on deep learning to develop automatically new models which can be used to detect other criminal activity as well. INSIKT is fit to become an important new tool in LEAs’ investigation and evidence gathering arsenal, giving them highly accurate, multilingual and real-time detection capabilities.
This project will allow us to improve INSIKT, integrate it with existing LEA tools and commercialize it, addressing the needs of the €60+B security market, with the effect of creating 50+ jobs and €11.7M annual revenue within 5 years from market launch.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- social sciences political sciences political transitions terrorism
- social sciences economics and business business and management entrepreneurship
- social sciences law law enforcement
- natural sciences computer and information sciences data science data mining
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.3.7. - Secure societies - Protecting freedom and security of Europe and its citizens
MAIN PROGRAMME
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H2020-EU.2.3.1. - Mainstreaming SME support, especially through a dedicated instrument
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-2 - SME instrument phase 2
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-SMEInst-2016-2017
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
08020 Barcelona
Spain
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.