Bd
B.J.E. de Bruin
info
Please Note
<p>This page displays the records of the person named above and is not linked to a unique person identifier. This record may need to be merged to a profile.</p>
2 records found
1
Student report
(2025)
-
C. Hernando De La Fuente, K.J. Trouwee, M.P. Jimenez Moreno, S.X. Li, M.A. Narkar, B.V. van Vliet, Amir Niknam, B.J.E. de Bruin
The spread of climate change mis- and disinformation poses a big threat to society; addressing this is the goal of the Joint Interdisciplinary Project (JIP) 6.1.1, in collaboration with the National Police. This report details the development of the Climate Disinformation Tracker, an open-source proof-ofconcept tool designed to trace the earliest online occurrence of climate denial narratives on Platform X and provide insightful visualizations of related tweets. The methodology, adapted from the DisTrack architecture, utilizes KeyBERT for keyword extraction and a custom scraping pipeline relying on the Nitter front-end for data retrieval, followed by mDeBERTa-v3-base-mnli-xnli for natural language inference (NLI) to classify posts as entailing, neutral, or contradictory to a user-provided claim. Validation testing demonstrated that the tool correctly identified the source tweet in 72% of claims when incorporating the synonym component, thus validating the potential of this approach for misinformation
tracking. The primary constraints identified are the dependence on non-deterministic Nitter scraping, which introduces operational instability and a 500-character query limit, and the accuracy ceiling of the alignment model. Despite these limitations, the tool validates a functional approach for empowering the public and investigative journalists with traceable context. ...
tracking. The primary constraints identified are the dependence on non-deterministic Nitter scraping, which introduces operational instability and a 500-character query limit, and the accuracy ceiling of the alignment model. Despite these limitations, the tool validates a functional approach for empowering the public and investigative journalists with traceable context. ...
The spread of climate change mis- and disinformation poses a big threat to society; addressing this is the goal of the Joint Interdisciplinary Project (JIP) 6.1.1, in collaboration with the National Police. This report details the development of the Climate Disinformation Tracker, an open-source proof-ofconcept tool designed to trace the earliest online occurrence of climate denial narratives on Platform X and provide insightful visualizations of related tweets. The methodology, adapted from the DisTrack architecture, utilizes KeyBERT for keyword extraction and a custom scraping pipeline relying on the Nitter front-end for data retrieval, followed by mDeBERTa-v3-base-mnli-xnli for natural language inference (NLI) to classify posts as entailing, neutral, or contradictory to a user-provided claim. Validation testing demonstrated that the tool correctly identified the source tweet in 72% of claims when incorporating the synonym component, thus validating the potential of this approach for misinformation
tracking. The primary constraints identified are the dependence on non-deterministic Nitter scraping, which introduces operational instability and a 500-character query limit, and the accuracy ceiling of the alignment model. Despite these limitations, the tool validates a functional approach for empowering the public and investigative journalists with traceable context.
tracking. The primary constraints identified are the dependence on non-deterministic Nitter scraping, which introduces operational instability and a 500-character query limit, and the accuracy ceiling of the alignment model. Despite these limitations, the tool validates a functional approach for empowering the public and investigative journalists with traceable context.
Breaking Hierarchical Barriers to Improve Collective Intelligence
Exploring Artificial Swarming Intelligence within the Dutch National Police
Student report
(2024)
-
Bas Dekkers, Bader Fissoune, A.A. Kuber, R.G. Mihălăchiuţă, M.J. Rottier, P. Schaefers, Amir Niknam, B.J.E. de Bruin
Today, huge volumes of information flow at unprecedented speeds, and large organisations like the Dutch National Police face significant challenges. Efficiently sharing, processing, and prioritizing information is essential but has become increasingly difficult to achieve. These chal- lenges often hinder their ability to make sound and timely decisions. This study investigates innovative methods to enhance collaborative decision-making within such complex environ- ments.
The main goal of this study is to research and test the potential of Artificial Swarming Intelli- gence to enable collective ranking of information based on its importance. The resulting Proof of Concept offers a new method for improving the efficiency of information sharing, enhancing collective intelligence, and facilitating the decision-making processes within the police force.
Drawing inspiration from natural swarming behaviour seen in species like bees, the platform allows participants to rank multiple pieces of information during collaborative sessions. This process helps to highlight the most significant topics, enabling quicker access to critical in- sights.
The Proof of Concept is structured as a digital platform designed to improve real-time decision- making. For our case study, we focused on the policy advisors of the Dutch National Police. The Proof of Concept operates as a client-server model, ensuring that user interactions are efficient while providing live updates on rankings. This allows participants to engage actively and see the evolving importance of various pieces of information.
However, despite the progress achieved, several limitations became evident. First, some envisioned functionalities were not fully developed or implemented within the project’s time frame. In addition, current design faces challenges in scalability, particularly when engaging larger groups of users. Issues related to user accessibility and potential biases in decision- making processes also came into view. To guide further work, we have highlighted key areas for future research and provided specific considerations that address these limitations, aiming to support the Proof of Concept’s development into a complete and fully scalable platform.
Ultimately, this Proof of Concept presents a promising approach to enhancing decision-making processes at the Dutch National Police. It lays the foundation for future research and devel- opment, with opportunities to refine its functionality and expand its use within the organisation. By improving how information is shared and prioritised, the Dutch National Police can enhance its collective intelligence and improve its decision-making processes. ...
The main goal of this study is to research and test the potential of Artificial Swarming Intelli- gence to enable collective ranking of information based on its importance. The resulting Proof of Concept offers a new method for improving the efficiency of information sharing, enhancing collective intelligence, and facilitating the decision-making processes within the police force.
Drawing inspiration from natural swarming behaviour seen in species like bees, the platform allows participants to rank multiple pieces of information during collaborative sessions. This process helps to highlight the most significant topics, enabling quicker access to critical in- sights.
The Proof of Concept is structured as a digital platform designed to improve real-time decision- making. For our case study, we focused on the policy advisors of the Dutch National Police. The Proof of Concept operates as a client-server model, ensuring that user interactions are efficient while providing live updates on rankings. This allows participants to engage actively and see the evolving importance of various pieces of information.
However, despite the progress achieved, several limitations became evident. First, some envisioned functionalities were not fully developed or implemented within the project’s time frame. In addition, current design faces challenges in scalability, particularly when engaging larger groups of users. Issues related to user accessibility and potential biases in decision- making processes also came into view. To guide further work, we have highlighted key areas for future research and provided specific considerations that address these limitations, aiming to support the Proof of Concept’s development into a complete and fully scalable platform.
Ultimately, this Proof of Concept presents a promising approach to enhancing decision-making processes at the Dutch National Police. It lays the foundation for future research and devel- opment, with opportunities to refine its functionality and expand its use within the organisation. By improving how information is shared and prioritised, the Dutch National Police can enhance its collective intelligence and improve its decision-making processes. ...
Today, huge volumes of information flow at unprecedented speeds, and large organisations like the Dutch National Police face significant challenges. Efficiently sharing, processing, and prioritizing information is essential but has become increasingly difficult to achieve. These chal- lenges often hinder their ability to make sound and timely decisions. This study investigates innovative methods to enhance collaborative decision-making within such complex environ- ments.
The main goal of this study is to research and test the potential of Artificial Swarming Intelli- gence to enable collective ranking of information based on its importance. The resulting Proof of Concept offers a new method for improving the efficiency of information sharing, enhancing collective intelligence, and facilitating the decision-making processes within the police force.
Drawing inspiration from natural swarming behaviour seen in species like bees, the platform allows participants to rank multiple pieces of information during collaborative sessions. This process helps to highlight the most significant topics, enabling quicker access to critical in- sights.
The Proof of Concept is structured as a digital platform designed to improve real-time decision- making. For our case study, we focused on the policy advisors of the Dutch National Police. The Proof of Concept operates as a client-server model, ensuring that user interactions are efficient while providing live updates on rankings. This allows participants to engage actively and see the evolving importance of various pieces of information.
However, despite the progress achieved, several limitations became evident. First, some envisioned functionalities were not fully developed or implemented within the project’s time frame. In addition, current design faces challenges in scalability, particularly when engaging larger groups of users. Issues related to user accessibility and potential biases in decision- making processes also came into view. To guide further work, we have highlighted key areas for future research and provided specific considerations that address these limitations, aiming to support the Proof of Concept’s development into a complete and fully scalable platform.
Ultimately, this Proof of Concept presents a promising approach to enhancing decision-making processes at the Dutch National Police. It lays the foundation for future research and devel- opment, with opportunities to refine its functionality and expand its use within the organisation. By improving how information is shared and prioritised, the Dutch National Police can enhance its collective intelligence and improve its decision-making processes.
The main goal of this study is to research and test the potential of Artificial Swarming Intelli- gence to enable collective ranking of information based on its importance. The resulting Proof of Concept offers a new method for improving the efficiency of information sharing, enhancing collective intelligence, and facilitating the decision-making processes within the police force.
Drawing inspiration from natural swarming behaviour seen in species like bees, the platform allows participants to rank multiple pieces of information during collaborative sessions. This process helps to highlight the most significant topics, enabling quicker access to critical in- sights.
The Proof of Concept is structured as a digital platform designed to improve real-time decision- making. For our case study, we focused on the policy advisors of the Dutch National Police. The Proof of Concept operates as a client-server model, ensuring that user interactions are efficient while providing live updates on rankings. This allows participants to engage actively and see the evolving importance of various pieces of information.
However, despite the progress achieved, several limitations became evident. First, some envisioned functionalities were not fully developed or implemented within the project’s time frame. In addition, current design faces challenges in scalability, particularly when engaging larger groups of users. Issues related to user accessibility and potential biases in decision- making processes also came into view. To guide further work, we have highlighted key areas for future research and provided specific considerations that address these limitations, aiming to support the Proof of Concept’s development into a complete and fully scalable platform.
Ultimately, this Proof of Concept presents a promising approach to enhancing decision-making processes at the Dutch National Police. It lays the foundation for future research and devel- opment, with opportunities to refine its functionality and expand its use within the organisation. By improving how information is shared and prioritised, the Dutch National Police can enhance its collective intelligence and improve its decision-making processes.