Interactions Research Group

Social media platforms have become the new public squares, wielding massive influence over how billions of people consume information, form opinions, and take decisions. Yet, beneath the surface of these seemingly personalized experiences lies a profound challenge: the algorithms powering these platforms don’t just recommend content—they shape worldviews, amplify divisions, and steer societal discourse.

This thesis examines the systemic risks associated with personalized recommender systems on Very Large Online Platforms (VLOPs). While these systems are designed to enhance user engagement through content personalization, they often lead to unintended consequences, such as the formation of filter bubbles, distortion of public opinion, and increased societal polarization. Despite new regulations in the EU, such as the Digital Services Act (DSA), which promote data transparency and accountability from VLOPs, researchers continue to face significant barriers in accessing platform data from platforms like X (formerly Twitter), Instagram, TikTok, and others.

By employing black-box testing as a methodological framework, this project focuses on identifying, analyzing, assessing, and mitigating systemic risks. Additionally, it evaluates the effectiveness of the DSA in enabling meaningful research on these issues. Given the pivotal role of social media in shaping public discourse—especially during the major global elections of 2024 and the enforcement of the DSA—this research is both timely and critical.

In this interdisciplinary project, you will work at the crossroads of Computer Science, Legal/Platform Regulations, and Social Sciences. While the main focus lies in Computer Science, the project integrates insights from platform governance and societal impact to build a system/framework for evaluating systemic risks in Personalized Recommender Systems.

This framework will address key challenges in assessing the societal, ethical, and technical implications of recommender systems, contributing to state-of-the-art methods for evaluating their impact. You will have the opportunity to leverage your technical skills while exploring the broader regulatory and social dimensions of this critical field.

This project is great for you, if you are:

• Passionate about or familiar with data scraping tools and working with social media data.
• Interested in social media platforms and their recommender systems, and curious about how they shape information consumption.
• Enthusiastic about regulations like the Digital Services Act (DSA) and their potential on data access.
• Drawn to exploring events and trends influencing the future of social media platforms.
• Looking to publish your work in academic venues and gain experience in impactful research dissemination.

Unsure about the topic? See here for additional readings:

• DSA: reclaimingautonomyonline.notion.site/Researcher-access-to-platform-data-under-the-DSA-Questions-and-answers-8f7390f3ae6b4aa7ad53d53158ed257c
• Systemic Risks: algorithmwatch.org/en/researching-systemic-risks-under-the-digital-services-act/  
• Scrutinizing Social Media Platforms: www.wsj.com/tech/tiktok-israel-gaza-hamas-war-a5dfa0ee  
• SOAP: www.alexandria.unisg.ch/entities/publication/f41060db-3d3b-4071-ad92-8ac6bb1cc734

Reach out if you're interested!

Luka Bekavac: lukajurelars.bekavac@unisg.ch
Prof. Simon Mayer: simon.mayer@unisg.ch

The personalization of an interface in Mixed Reality (MR) can be very beneficial for users since it, e.g., enables them to use the interface based on their abilities and capabilities, or to interact more efficiently. Personalization describes the adaptation of a system based on personal data (e.g, demographics, level of expertise, real-time physiological data, user context data). For instance, to control a robotic arm in a human-robot collaboration scenario, an expert user could see a more complex interface with more fine-grained control options than a novice user. Additionally, the interface might be adapted based on their preferred language, current cognitive state, or the task they are currently performing. However, users might not know why the interface is adapted, if they are not informed about it in a well-designed manner. Especially when many parameters are part of the personalization, it can be challenging to design an appropriate interface that does not lead to an increased cognitive load for users. Therefore, we are interested in studying how users can be informed transparently about why and how an interface has been personalized for them, to increase their trust in the system and potentially to let users adapt the personalization parameters.

In this project, you will:

• Review existing approaches for informing users transparently about why and how an (MR) interface has been personalized for them
• Design and create mock-ups of these interface designs (e.g., using Figma or Penpot)
• Conduct and evaluate in person and online surveys to measure people’s preferred design(s) based on the created mock-ups
• Implement the preferred designs (based on the survey results) of transparent personalization communication in an MR application for the Microsoft HoloLens 2 using Unity
• Conduct and evaluate a user study to measure people’s preferred design(s) in one or multiple concrete scenarios

If you are a Master's student, you will additionally:

• Additionally implement options for users to adapt the personalization parameters ("customization").
• Conduct and evaluate a user study to evaluate the transparent design and the adaption of personalization parameters.

This project is great for you, if you are:

• Strongly interested or familiar in designing Mixed/Augmented Reality interfaces
• Familiar with visual design tools (e.g., Adobe Photoshop, Figma, Penpot, or Affinity Designer)
• Interested in Personalization, Transparency & Technology
• Interested in participating in state of the art research
• Interested in publishing your research work in academic venues
• An excellent communicator in English

Reach out if you are interested!

Jannis Strecker jannisrene.strecker@unisg.ch

Solid (Social Linked Data) is a specification to create a decentralized data platform for Web applications; its objective is to allow the management of users’ data independently of the applications that create and consume such data: Applications are decoupled from the data they use.

To realize Solid, users' data is stored in a Web-accessible personal online datastore: a Pod. Developers can use the Solid protocol based on existing W3C (World Wide Web Consortium) recommendations for reading, writing, and controlling (e.g., access control) the contents of users’ Pods. Users are able to grant access to their data, and have the option to stop sharing their data or switch between applications at any time [1].

Mixed Reality (MR) devices such as the Microsoft HoloLens 2 (HL2) are often equipped with capabilities that can track personal data such as eye trackers that allow to record a user's gaze behavior. Such data is personal and highly sensitive, since it can be used to not only estimate the activity that a user currently performs, but also to estimate other personal information of the user, from drug consumption to cultural background [2]. Thus, to avoid creating several copies of the data and sharing them with others through traditional means (e.g., a Data Controller that runs a gaze-sharing platform), the use of Solid enables a user to retain control about where their data is and who accesses it.

We developed the Solid Interaction Library for C# which includes all basic functions to interact with Solid Pods directly from a HL2. However, this library does not include any user interface elements.

With this thesis, we explore the integration of Solid and MR using an HL2. Concretely, this thesis implements an application for the HL2 that provides an MR UI for interacting with a Solid Pod. The implemented app furthermore provides an intuitive way to share data from the HL2 in real-time with others via Solid. This may include, e.g, one's current gaze data, current activity or detected objects in the user's environment.

[1] Sambra, Essam Mansour, Sandro Hawke, Maged Zereba, Nicola Greco, Abdurrahman Ghanem, D. Zagidulin, Ashraf Aboulnaga, and T. Berners-Lee. Solid : A Platform for Decentralized Social Applications Based on Linked Data. 2016.

[2] Jacob Leon Kröger, Otto Hans-Martin Lutz, and Florian Müller. What Does Your Gaze Reveal About You? On the Privacy Implications of Eye Tracking. In Michael Friedewald, Melek ¨Onen, Eva Lievens, Stephan Krenn, and Samuel Fricker, editors, Privacy and Identity Management. Data for Better Living: AI and Privacy, volume 576, pages 226–241. Springer International Publishing, Cham, 2020.

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This project is great for you, if you are:

• Strongly interested or familiar in designing Mixed Reality interfaces
• Interested in Privacy, Decentralized data storage & Technology
• Interested in participating in state of the art research
• Interested in publishing your research work in academic venues
• An excellent communicator in English

Reach out if you are interested!

Jannis Strecker: jannisrene.strecker@unisg.ch
Dr. Kimberly Garcia: kimberly.garcia@unisg.ch

Are you interested in digital health and market research? We offer the possibility of empirically conducting market research and strategic planning for a nutrition-related start-up. The master thesis should develop a scientifically sound and comprehensive concept for the start-up’s business plan. The details about the start-up will be communicated to the student doing the thesis.  

What will you do?

1. Identify target market segments and market size
2. Analyze the competitive landscape
3. Assess market trends and opportunities
4. Evaluate user needs and preferences
5. Develop a strategic business plan

Why join us?

1. Work on a project at the intersection of health, technology, and market research.
2. Real-world impact: Your research will directly influence the development and success of a start-up.
3. Professional development: Gain valuable experience in market research methodologies, data analysis, and strategic planning.
4. Supportive environment: Collaborate with a team of experienced professionals and mentors who are dedicated to your success.

Who are we looking for?

• Strongly interested in the business side of digital health
• Interested in participating in state-of-the-art research
• Interested in publishing your research work in academic venues
• Proficient in English and German

Contact Information
For more information, please contact Jing Wu at jing.wu@unisg.ch

Application Deadline
25/07/2024