The G7 is obviously concerned with overarching political and economic political, economic and security matters, but it is concerned also with various other topics like investment in growth, jobs for the future, gender equality, climate change, and clean energy.
Canada feels that it is important to understand what people think about these subjects and whether they react positively or negatively about them country by country.
Canada turned to OpenText (which is, of course, a Canadian company) to apply its data analytics skills to data collected from publicly-available sources such as G7 articles and tweets. To do this, OpenText uses Magellan, it’s artificial intelligence (AI)–powered analytics platform, to retrieve documents, display sentiment, and break down the key themes in an interactive way to show what issues matter most to citizens.
OpenText is, among other things, an eDiscovery company – it appeared most recently in this blog in the context of its sale to the UK Serious Fraud Office of its Axcelerate eDiscovery software (I wrote about that here). The nature of a modern eDiscovery exercise is that it embraces tweets, Facebook posts, chat and other social media sources as well as emails and more conventional documents
Analysis of kind used in the G7 example may be relevant to any type of claim, but it is particularly relevant where fraud is concerned, not least because the parties are unlikely to be open in correspondence about their intentions and discussions. It becomes more necessary to draw conclusions from less concrete things than keywords and names.
The use of eDiscovery skills and tools for wider purposes is a recurring theme in this blog. OpenText’s G7 analysis is a good example of this.