Twitter streams have been extensively studied in various contexts, such as sentiment analysis (Kouloumpis et al., 2011), stock market prediction (Nguyen and Shirai, 2015) and traffic detection (D'Andrea et al., 2015).
for sub-event detection in Twitter, several approaches Figure 1: Our sub-event detection model comprises: (a) a bin layer, (b) a unit layer, (c) a word embeddings layer, (d) a representation layer and (e) a chronological LSTM layer to model the natural flow of the sub-events within the event.