Before revision:  We fill this gap by releasing a dataset of 5000 English news headlines annotated via crowdsourcing with their dominant emotions, emotion experiencers and textual cues,  emotion causes and targets, as well as the reader's perception and emotion of the headline.
After revision:  We fill this gap by releasing a dataset of 5000 English news headlines annotated via crowdsourcing with their associated emotions, the corresponding emotion experiencers and textual cues, emotion causes and targets, as well as the reader's perception and emotion of the headline.