| Proj No. | A1055-251 |
| Title | Event Detection from Social Media Using Machine Learning and Natural Language Processing |
| Summary | Social media platforms such as X generate vast amounts of real-time data, making them valuable sources for detecting and tracking events. Events such as natural disasters, political protests, or public health emergencies often emerge first on social media before traditional news outlets. This proposal aims to develop an automated event detection system leveraging machine learning (ML) and natural language processing (NLP) techniques to extract relevant event-related information from social media streams. |
| Supervisor | A/P Mao Kezhi (Loc:S2 > S2 B2C > S2 B2C 84, Ext: +65 67904284) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Internet of Things Laboratory (Loc: S1-B4c-14, ext: 5470/5475) |
| Single/Group: | Single |
| Area: | Digital Media Processing and Computer Engineering |
| ISP/RI/SMP/SCP?: |