Depending on the number of students and the project scope, the project can also include:
• Development of data processing pipelines for large-scale analysis of emoji usage and co-occurrence patterns in social media data
• Implementation of models for emoji-aware sentiment or emotion classification
• Design and implementation of a chat-based experimental setup
• Evaluation of emotional clarity and misinterpretation in text-only vs. text+emoji conditions
Upon completion of this project, we will work hand in hand to publish the results in a well-established conference or journal in Human–Computer Interaction (HCI).
• Good programming skills in Python
• Basic knowledge of data analysis and/or machine learning
• Interest in human–computer interaction, social media, or affective computing
• (Preferably) experience with NLP, data analysis, or experimental study design
| Frequency | Weekday | Time | Format / Place | Period | |
|---|---|---|---|---|---|
| by appointment | n.V. | 13.04.-24.07.2026 | Nach Vereinbarung, online, CITEC oder R.1 |
| Module | Course | Requirements | |
|---|---|---|---|
| 39-M-Inf-INT-app-foc_a Applied Interaction Technology (focus) Applied Interaction Technology (focus) | Applied Interaction Technology (focus): Project | Study requirement
|
Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.