In contrast, our work does take into account that chronological order and we predict the presence and the type of a sub-event exploiting information from previous tweets.
we (i) propose a new neural baseline model that outperforms the state-of-the-art performance on the binary classification problem of detecting the presence/absence of sub-events in a sports stream, (ii) establish a new reasonable baseline for predicting also the sub-event types, (iii) explicitly take into account chronological information, i.e., the relation among consecutive tweets, by framing sub-event detection as a sequence labeling problem on top of our baseline model, and (iv) perform an experimental study, indicating the benefit of sequence labeling for sub-event detection in sports Twitter streams.