How Toronto's Buzz Indexes uses the power of machine learning to mine social media's big data sets

One Toronto firm is using cognitive artificial intelligence (AI) processes to mine big data sets in social media to help asset management firms make better decisions for investors. Based in Toronto, Buzz Indexes claims that machine learning has evolved to the point where developing models to monitor and understand the context within the millions of posts and comments around stocks and investments made on online social media platform such as Twitter is a reality. The company initially launched its Buzz Social Media Insights Index this past spring and offers regular methodology and stock rebalancing updates, most recently this past month. According to Buzz Indexes founder Jamie Wise, the offering takes a big data approach to social media such as Twitter, aggregating chatter on investment opportunities to track potential actionable insights: "Each month we look at an index of the 100 most talked about stocks in the media landscape and the tone and depth of the conversation," he said. Specifically, the firm reviews social media platforms, online news sites and web forums to identify "influencers" whose tweets, comments and posts are most likely to impact collective opinion.