This video describes the process of assessing and utilizing BotDetector results.
BotDetector flags communicators with a high ratio of emails sent vs. those received.
Mass-senders not getting many reciprocal interactions are often junk emails that can be more effectively and efficiently reviewed outside of the standard review workflow.
Several fields are automatically populated on documents flagged by BotDetector.
The “Bot” field indicates the name of the sender, while the “Document Count” field reflects how many documents the potential bot is present on.
The “Average Communication Count” shows this interaction ratio. A count of one point zero (1.0) means the sender never received a response or forward.
The “Has Non-Bot Sender” field indicates if the instance is one of the few communications where the bot did receive an interaction.
The “Bot” tab reflects results for the entire set, while the fields allow for the assessment of any subset of documents via searches.
Prioritizing the bots with the largest document counts can have a significant impact early in the review process.
Often the results will include daily newsletters, promotional offer emails, and things such as travel confirmations that are apparent from the bot name.
Depending on the nature of the review, these may suppressed from review or handled in mass as non-relevant.
The instances that are not facially obvious as junk may need to be sampled to determine potential relevance.
The results also can include internal communications and notifications that may have a higher likelihood of relevance. If necessary, these can be isolated using the “Email Domain” field for a higher level of scrutiny.
Instances that that are determined as substantive, or potentially relevant to the matter at hand, can be sent on to the standard review process.
A point may also be reached where there isn’t utility in reviewing the small Bot groups outside of the normal workflow. At this stage, these bot documents and their attachments can be pushed to the standard review.