Web Science Seminar

October 10th, 2023

Web Science is an advanced interdisciplinary field that intersects computer science, mathematics, sociology, economics, and other fields.

This seminar explores aspects of the World Wide Web, focusing on cutting-edge research in Web Analytics, Web Engineering, and aspects of Web Science that may lead to thesis topics for students.
The seminar covers a variety of areas such as algorithms and research for social aspects of the web such as recommender systems, social network analysis, and data mining as well as chatbots. A large part then is the educational web with mixed reality and psychomotor learning and the detection of academic trends. Lastly, software development trends are covered for web trust & credibility, web APIs & protocols, web-based software development models, and data security.

The seminar offers the following research topics:
First, we cover fundamental principles and latest advances in web development and design. You will explore modern data exchange APIs and the development of web platforms for civic engagement as well as the integration of chatbot and conversational agent technologies into the web landscape. This includes the convergence of AI (NLP, LLMs) and data analytics in Web Science.
The second topic is about social network analysis and data mining. This includes determining online communities and influential individuals along with their evolution over time on or across social networks. Additionally, it covers tools for mining information from increasingly decentralized and closed up sources online and the feasibility of AI agents and algorithms aiding the collection process.
The educational web is another large topic. From recent advances in learning technologies such as mixed reality in learning educational design over learning spaces and research tools and academic trend detection.
Finally, we cover recommender systems for educational and private applications as well as information security in academics via blockchain, and web trust. These areas are often explored via machine learning and recently LLM resources.

Over the course of the seminar, you will write your paper and deliver a presentation on your chosen topic, benefiting from the constructive feedback of both peers (via an own peer review) and advisors.
Upon completing this seminar, you will have achieved a comprehensive understanding of the selected topics within Web Science.

The seminar starts with a kickoff meeting, you will vote for a topic that aligns with your interests from a range of Web Science areas. After this you will receive access to LaTeX templates in CI/CD in a GitLab repository for writing your paper. You will be paired with an advisor who will provide support throughout all stages of the seminar. They will give you feedback from initial research and paper until the preparation and delivery of your final presentation.

Topic Assignment

Topic Supervisor Student Reviewer
Advancing User Modeling with Retrieval-Augmented Generation and Large Language Models Fathi 384347
Approaches to WebXR Hensen 421978
Community Detection Applications in Knowledge Graphs Kißgen 453355
Comparison of Modern Data Exchange APIs Neumann 444969
Current State of Federated Identity Management Kißgen 406454
Data Marketplaces – Opportunities and Challenges for Distributed Ledger Technology usage in Distributed Data Analysis Slupczynski 445838
Dynamic Knowledge Integration for Real-Time Recommendations Fathi 434661
Graph Analysis on Multidimensional Social Networks Kißgen 453327
Leveraging LLMs to enhance personality-based recommender systems Fathi 445448
Substituting and Complementing Mapping Languages with LLM Functionality Belova 424124