COVID-19 & Election

These datasets were used in the paper 'Evaluation of Thematic Coherence in Microblogs' (ACL, 2021). The data is structured as follows: each file represents a cluster of tweets which contains the tweet IDs, the journalist annotations for quality evaluation and issue identification, as well as the metric evaluation scores. Note that a set of 50 clusters, equally split between COVID-19 and Election domains, is shared between the 3 annotators and thus contains 3 labels.

Each cluster of tweets is evaluated for its thematic coherence quality (3-point scale) and for its issue identification (Intruded, Chained or Random). For more information about the annotation scheme, please refer to the complete annotation guidelines (available at https://doi.org/10.6084/m9.figshare.14703471) or the paper.

Potential uses for these datasets are in the evaluation of thematic coherence, topic modelling and text summarisation fields.