by Tom Groom - D4 on March 20, 2015
Our team sometimes gets asked about reviewing text messages, and one of our Premium Hosting Partners, D4, recently put together an awesome blog post that addresses the issue. We wanted to share it with all of you. The post was originally published on D4’s Discover More blog in January.
There are very few people today who don’t thumb text messages on their phones. We tend to treat text messages as if they can’t be retrieved once we hit send. “Nobody will find this” one may tell themselves. Oh really? What happens when opposing counsel requests that text messages are included from one of your key custodians? At first, you object in that your client’s text messages are not “reasonably accessible,” but that argument isn’t as easy to win as it used to be. Once you’ve accepted the fact that review of the text messages is going to happen, the question hits you—“How can text messages most efficiently be reviewed?”
The answer may surprise you. Think of each individual text message as a record (like an email or Word document). If properly collected, each text message record has metadata associated with it that can be used to stitch together the bigger story. Text message timeframes are normally measured in seconds (rather than days, as with email), so they are often reviewed in a separate database than email or scanned documents. The key for efficient text message review is to have a common “date and time” field to sort the messages in order to create a conversation. This is especially true if messages for more than one custodian are being reviewed. Another key is to leverage relational fields that can be used to associate phone numbers to participants, as well as to enable “group and pivot” reports between phones, participants, timeframes, and even conversational tone.
The screenshots below show how to review text messages in Relativity, one of the hosted review platform options offered by D4. Text messages from three different phones were placed into this database. From here, the reviewer can choose which phones to include, as well as which participants to include in the query. Sorting by date and time will piece together the text messages between parties, which can help establish intent and/or reveal interesting behavior.
Using the Pivot feature in Relativity, one can analyze which participant created the most messages.
By grouping on participant and pivoting on “tone,” one can determine which messages are sent and received for business or personal purposes, and with analytics, the type of conversational tone used in the message, such as “aggressive” or “flirtatious.” Pretty cool.
The next time you uncover opposing custodians using text messaging, and have reason to believe there are facts important to the case that may only be found in text messages, don’t be afraid to include that in your ESI request. Also, now that you know there are simple workflows that can handle multiple people using text, you may want to ask your client for the same to help your side of the story.
What unique data types have you had to address during review? Let us know in the comments.