Ensembled convolutional neural network models for retrieving flood relevant tweets

Social media, which provides instant textual and visual information exchange, plays a more important role in emergency response than ever before. Many researchers nowadays are focusing on disaster monitoring using crowd sourcing. Interpretation and retrieval of such information significantly influences the efficiency of these applications. This paper presents a method proposed by team EVUS-ikg for the MediaEval 2018 challenge on Multimedia Satellite Task. We only focused on the subtask "flood classification for social multimedia". A supervised learning method with an ensemble of 10 Convolutional Neural Networks (CNN) was applied to classify the tweets in the benchmark. Copyright held by the owner/author(s).