Content analysis of asynchronous discussions can help to detect cognitive presence in online discussions (Kovanović et al, 2016), and institutions can also learn new information about student learning to enhance educational conditions related to student success (Baer & Campbell, 2012). The trends and insights obtained from such analyses could be used for improving teaching and learning efficacy. Therefore, a growing number of researchers are investigating student discourse to understand classroom interactivity and the level of participant understanding.

Since the authors have information about time, the authors can add more relations to the database, e.g. about which event instances precede others, as indicated by green arrows in this picture: This completes the transition from the text domain of documents to the “idea world” of canonical events and entities, references to/instances of these, and relationships between these instances.

The Recorded Future system contains many components, which are summarized in the following diagram: The system is centered round the database, which contains information about all canonical event and entities, together with information about event and entity references, documents containing these references, and the sources from which these documents were obtained

We have decided on the term “temporal analytics” to describe the time oriented analysis tasks supported by our systems