H2020Индивидуална стипендия2021–2023

Dia-Pol · Polarization or dialogue? A deep learning study of the Black lives matter and Me Too online social movements

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2021-07-01 → 2023-11-21
Финансиране от ЕС: 145 356 €
Участници: 1
Схема: MSCA-IF

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Накратко на български

Взаимодействията между социалните движения, като Black Lives Matter и Me Too, показват дали онлайн дискусиите водят до диалог или до разделение. Разбирането на тези процеси помага за ограничаване на ескалацията на конфликтите и борба с дезинформацията в мрежата.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Dia-Pol: Polarization or dialogue? A deep learning study of the Black lives matter and Me Too online social movements

This study explored whether interactions between social movements yield polarization or encourage dialogue using the cases of the Black Lives Matter (BLM) and Me Too (MT) movements. The project had 3 objectives: (a) pioneer a novel research agenda on the dynamics of movement interactions, filling a void in political science, sociology, communication, and race and gender studies; (b) devise an algorithm to aid stakeholders, e.g., citizens, activists and NGOs, in identifying divisive issues and crafting messages to navigate sensitivities; and (c) advance computational social science (CSS) within political science and at the host university by establishing a CSS lab at Bogazici. Studying how social movements interact with each other and with their countermovements is crucial for understanding and mitigating polarization, especially on issues like race and gender since even basic demands for equality can be misconstrued and weaponized by extremist groups. Recent events, e.g., the Kyle Rittenhouse trial, demonstrate how right-wing groups can distort BLM's messages. Understanding how these distortions occur is essential for developing strategies to counter them. By analyzing social movement interactions, we can identify how disagreements escalate, how misinformation spreads, and how echo chambers amplify extreme views. Understanding these processes helps develop more effective strategies for de-escalating tensions and fostering dialogue. In a polarized environment, NGOs and activists must frame messages clearly and concisely, while being mindful of how their words might be misinterpreted. Dia-Pol’s algorithm helps identify the key themes and concerns in public discourse. This information, now available on the Dia-Pol platform, can be used to strategically craft messages. Also, political science, sociology, communication, and data science play important roles in understanding and mitigating polarization. To foster interdisciplinary collaboration and promote CSS, this project organized workshops and training. This project utilized open science practices (GitLab) for data analysis. It developed a novel theory to study variations within countermovements, examined the effect of BLM protests on state-level policing reforms and court decisions, and studied the media coverage of BLM protests.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

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.

Оригинален текст от CORDIS (на английски).

Участници

BOGAZICI UNIVERSITESI · IstanbulКоординаторТурция