Text Messages

This technical note explains the processing and options available for reviewing text messages in the Lexbe eDiscovery Platform (LEP):

1) During the automated processing
clustered string contents of text messages will be extracted from devices such as iPhones, and merged into one document in Excel parsing on metadata field values (Type, Sender, Recipient, Text, Subject, etc.)


2) Technical Services also offers further
extraction and processing of active text messages to manually break apart, recombine and restructure each text message into separate documents to make them look and act like an email (explained in more detail below).

Common Types of Text Messages

Text messages are native files generated by electronic devices such as cell phones, tablets, and instant message systems. They come in two forms: short message service (SMS) and multimedia messaging service (MMS). A standard text message is sent using SMS, which is usually no longer than 160 characters. MMS include not only text, but also images, video, and sound. Text messages can be stored and saved with different file formats as follows:

  •  .bbm (BlackBerry Messenger)
  •  .sms 
  •  .mms
  •  .ipa (iPhone and iPad)
  •  .mmssms.db, etc.

Text Message Challenges

Retrieving and extracting data from text messages is not always an easy process because of the accessibility of various message formats. In general, long messages are split into smaller messages by the sending device and concatenated at the receiving end; however, if the electronic device does not support the automatic splitting and concatenation of long SMS messages, then the processing will require manual extraction and conversion.

Reason to Manually Separate and Convert Text Messages

Each text message converted into an email allows the user to easily review documents, ensuring data is properly identified, preserved, and relevant for use in eDiscovery proceedings. We have also to consider that all arguments around inaccessibility, burden, or even privacy will be disregarded, especially when it to comes to preservation and collection of relevant ESI no matter what the source.

Using our eDiscovery Technical Services To Process Text Messages


Here are the steps Technical Services will take to manually process text messages:

Step 1: Extraction

We will extract the metadata (below) from each text message:
From:
To:
Date/Time Sent:
Message







Step 2: Associate Metadata

Associate extracted metadata with the following built-in fields:
Date Sent
Master Date
Author
Doc Type = (e.g.SMS, iMessage, etc.)

Step 3: Upload Text Messages

Those individual documents including a full text search will be uploaded to a case, which allows the user to easily review and tag as responsive, privileged, work-product, confidential, atty eyes only, etc. This step also generates a privilege log from fielded data within LEP, with links to the text messages converted into a specified review format (Native, Near-native TIFF, PDF, HTML); therefore, speeding preparation and internal review before production.