Localized Flood Detection With Minimal Labeled Social Media Data Using Transfer Learning
Table 1: Data Distribution
['[BOLD] Class Label', '[BOLD] Tweets Counts']
Data Visualization: Our focus here is to understand the basic characteristics of tweets and demonstrate the power of transfer learning method in this application. Although both of the datasets are similar in distribution thus, we have selected Queensland flood dataset for elaboration. By visual inspection of these most frequent words, bigram and trigram, we have a general understanding of the major topics and themes in the data. Tweets characteristics are generally similar in most of the cases so it is highly probable that it can be effectively applied for other scenarios or new location as well.