Sentiment Analysis is the latest AI tool to hit the eDiscovery market, and it is causing quite a stir!

Since its launch, the team here at Altlaw have been testing this new tool on a wide variety of documents to assess its capabilities and determine if it has a place in our eDiscovery processes. We are thrilled to say that, so far, we have found this tool to be very effective and we are looking forward to implementing it in our workflows to boost results for our clients.

As it looks like Sentiment Analysis is here to stay, we would like to take this opportunity to go into a little more detail about what Sentiment Analysis actually is, how it works and what you can expect from using it in your projects. 

What is Sentiment Analysis?

Sentiment Analysis is an AI tool within the RelativityOne platform that scores documents based on the likelihood that they contain indications of a pre-specified sentiment or multiple sentiments. The sentiments currently available to us within RelativityOne are positivity, negativity, anger and desire. Analysis of documents in this way allows us to build a deeper understanding of the context surrounding communications and allows us to detect unusual or anomalous interactions between key actors in your case.   

Sentiment Analysis can help boost the efficiency of your review in a couple of key ways. Firstly, it can provide a high-level overview of your documents, therefore allowing you to review them based on the type of documents that are likely to be relevant to your case. Secondly, it can help locate the catalyst documents that can change the course of your case by highlighting anomalous communications.