Detecting Rumors in Twitter for Humanitarian Activities

Detecting Rumors in Twitter for Humanitarian Activities

Vaporidis, Dimitrios-Marios (TU Delft Technology, Policy and Management)

Warnier, Martijn (graduation committee)
Huang, Yilin (mentor)
Cunningham, Scott (mentor)

Delft University of Technology

Engineering and Policy Analysis

2019-01-24

In this Master Thesis project, the objective is to study how can Supervised Machine Learning be used to detect text-based rumours for humanitarian activities in Twitter. A model was developed in this project in order to classify a tweet at question whether is a rumour or not and whether is relevant to humanitarian activities or not. The findings of this research were promising as the classification modules developed were able to score 75.8% in Recall classifying tweets to rumours and non-rumours and 96.6% in Recall classifying tweets to relevant to humanitarian activities and not relevant.

Humanitarian data
Supervised Learning
Twitter
Rumour Detection
Machine Learning

http://resolver.tudelft.nl/uuid:b20eeb6f-c28e-4163-ae2f-f42ca54b5004

Student theses

master thesis

© 2019 Dimitrios-Marios Vaporidis