Short message data comes from collaborative communication tools, with popular platforms including Slack, Teams, instant messaging, Bloomberg, SMS, and others. Numerous companies have embraced this communication mode due to its user-friendly nature, allowing both one-on-one and group channel interactions. While these tools have proven invaluable to users, particularly in a remote work environment, they have posed significant challenges in the realm of eDiscovery.
Short messages distinguish themselves from emails through their distinct tone and format. Given their collaborative nature, these conversations tend to be sporadic, lacking the structured thread-like organization found in emails. In the world of eDiscovery, which traditionally operates around the concept of "documents," exporting short message data involves generating a single document for each individual post. This approach results in a substantial volume of data that can be challenging to navigate due to its fragmentation.
This remained the case until Relativity introduced RSMF (Relativity's Short Message Format). RSMF leverages chat "strings" to keep conversations together in a single document, streamlining the review process for greater efficiency. It’s common practice to divide these "chat strings" into 24-hour segments for the sake of relevance and expedient review. This technological advancement enables short message data to be organized and presented in a user-friendly fashion.
Bonus: With RSMF clients no longer need Slack Enterprise licensing to access and export the data, saving them time and money.
The most recent development in the realm of short message review involves the integration of sentiment analysis in conjunction with RSMF. Email etiquette often mirrors the formality seen in traditional memos, whereas short messages, bear resemblance to informal "water cooler chat." They tend to be casual and candid, the perfect place for one to share their unfiltered feelings.
Sentiment analysis is a crucial tool that assesses the tone and emotional content of a conversation, categorizing it as either positive or negative. This technology demonstrates a high level of intelligence by considering the entire context of the conversation when determining its tone, rather than relying solely on the words used. This can help determine whether someone’s “feelings” are impactful on the case.
Managing short message data has been a persistent challenge since its inception. However, thanks to the technological advancements at our disposal, we can now transition towards more efficient solutions. Much like our other AI Insights, it's crucial to emphasize the significance of embracing AI in order to be successful within eDiscovery.
