JADS: PhD in Network Perspective on the Content and User Behavior (1,0 fte)

Jheronimus Academy of Data Science (JADS) Den Bosch, isproud to start with three large Robust AI labs together with:

JADS is seeking enthusiastic colleagues for the positions of PhD students. We operationalize the huge ambition around AI by explicitly aligning our research agenda on Robust AI with the United Nation's sustainable development goals.

The project is funded in a public-private partnership by NWO/NLAIC and private partners.
This position is part of the ResponsibleMedia Lab.

Description of the Responsible Media Lab (run jointly by UvA, JADS and DPG Media)
How can AI contribute to the functioning of the media along the entire production chain (sourcing, production, distribution, engagement), and even fundamentally change aspects of the media as we know it? The lab will explore the potential of AI-driven solutions for the media, their professional role, opportunities for new business models and new ways of engaging with users, while taking into account professional values and the emerging regulatory framework for AI. The lab seeks to develop AI-based methods and solutions that facilitate more diverse news offerings to readers, working alongside human journalists.

The lab is a collaboration between UvA, JADS and DPG media and consists of 5 PhD projects.
All PhD trajectories will focus on the development and evaluation of AI-based algorithms and tools to support responsible media production:

All the PhD students will closely interact with each other as the projects are complementary: they focus on either generating or better understanding the content, fueling further platform functionalities, or understanding interactions with the users of the platforms. While project
1, 3 and 4 focus on different aspects of the socio-technical system, project 2 and 5 are more focused on specific algorithms.

Short Description of the PhD project
Mass media and the contents they produce are a central part of everyone's life. A very diverse set of users consumes mass media content, while perceiving and acting upon it in various ways. Media content is driven by journalistic values and choices, as well as business ones. Exposure to the content affects the way users act in their everyday life. Yet understanding how the users perceive specific topics and themes in the content is far from being straightforward. This project capitalizes on network analysis to model the interconnection between the content and how users react to it by forming preferences to better understand both the content structure and the user behavior in relation to this content. The project further zooms onto the business users to explore how this deeper understanding can fuel new business opportunities.

JobDescription
You will work at the interface of natural language processing (NLP), network analysis and causal inference methods to reach a deeper understanding of the dynamics and implications of mass media exposure. Metrics for understanding the nature of the content (e.g., journalistic values and style) and modeling interactions of the users with the content of multiple platforms and business models will be developed and employed. In this project, we model the relational nature of the process of users engaging with content provided by heterogeneous platforms.

This project is embedded in the Data Entrepreneurship unit of JADS, one of the three research units next to Data Governance and Data Analytics.