Project description
A new way to explore Black Lives Matter and #MeToo
The role of social media in the emergence of social movements like Black Lives Matter and #MeToo cannot be underestimated, but it remains underexplored. So too is their interaction with counter-movements and their contribution to polarisation or dialogue. The EU-funded Dia-Pol project will fill this knowledge gap by examining the debates surrounding the two movements in Europe. It will check whether dialogue around intersectional (e.g. black gay men) or controversial (e.g. gender equality) themes are associated with liberal and progressive users, and if polarisation is linked to conservativism. The project will develop an algorithm operating on an interactive online platform to assist citizens, NGOs, and policymakers to address public sensitivities and tackle prejudices.
Objective
This project studies whether interactions on social media between social movements working for race and gender equality and their countermovements trigger polarisation or dialogue by applying topic modelling and deep learning techniques on big data. Specifically, I examine debates around the Black lives matter and Me Too movements in Europe with a focus on groups and individuals that are at their intersection––e.g. gay Black men, since such intersectional groups are subject to multiple and novel forms of domination due to the overlap of categories. I seek to find out whether dialogue dialogue forms around intersectional themes (e.g. respect to black gay men) or on less specific and controversial themes (e.g. gender equality) promoted by politically liberal and progressive users, and whether polarisation is associated with political conservativism. I aim to develop an algorithm to operate on an interactive online platform called Dia-Pol, to assist citizens, activists, NGOs, and decision makers, such as the European Commission, to find out which issues are the most polarising and how messages should be (re)shaped to address people’s sensitivities and avoid misunderstandings and deconstruct prejudices. This algorithm will generate information that can be incorporated into reports and studies, and will be applicable to other social media debates. This project is the first application of deep learning in political science and is one of the rare social science projects to use state-of-the-art computational techniques to test a rich theory. It foregrounds a powerful analytical tool that will be applicable to other social movement studies. Theoretically, it is the first study on intersectionality and echo chambers and on outcomes of movement interactions with their counter and synthetic movements. Therefore, its findings will start a novel research agenda. Also, the project will shift the focus away from studies of singular social movements to a comparative approach.
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: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- social sciences sociology social issues social inequalities gender inequality
- natural sciences computer and information sciences data science big data
- social sciences sociology social issues social inequalities racial inequality
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- social sciences political sciences
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.
-
H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
See all projects funded under this programme -
H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
See all projects funded under this programme
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.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
See all projects funded under this funding scheme
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-MSCA-IF-2020
See all projects funded under this callCoordinator
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.
34342 Istanbul
Türkiye
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.