We developed a machine-learning-based method to detect video game players that harass teammates or opponents in chat earlier in the conversation. This real-time technology would allow gaming companies to intervene during games, such as issue warnings or muting or banning a player. In a proof-of-concept experiment on League of Legends data we compute and visualize evaluation metrics for a machine learning classifier as conversations unfold, and observe that the optimal precision and recall of detecting toxic players at each moment in the conversation depends on the confidence threshold of the classifier: the threshold should start low, and increase as the conversation unfolds. How fast this sliding threshold should increase depends on the training set size.

Cross-document event chain co-referencing in corpora of news articles would achieve increased precision and generalizability from a method that consistently recognizes narrative, discursive, and phenomenological features such as tense, mood, tone, canonicity and breach, person, hermeneutic composability, speed, and time. Current models that capture primarily linguistic data such as entities, times, and relations or causal relationships may only incidentally capture narrative framing features of events. That limits efforts at narrative and event chain segmentation, among other predicate tasks for narrative search and narrative-based reasoning. It further limits research on audience engagement with journalism about complex subjects. This position paper explores the above proposition with respect to narrative theory and ongoing research on segmenting event chains into narrative units. Our own work in progress approaches this task using event segmentation, word embeddings, and variable length pattern matching in a corpus of 2,000 articles describing environmental events. Our position is that narrative features may or may not be implicitly captured by current methods explicitly focused on events as linguistic phenomena, that they are not explicitly captured, and that further research is required.