A typical show has thousands - maybe tens of thousands - of social media comments.
That's way too many to be read by viewers interested in engaging with social media while also enjoying video content. We developed Tomorrowish Machine Curation (TMC) to choose the best, most interesting comments to display. TMC looks at lots of things to determine the optimal stream of comments.
TheThe first and core layer of TMC. This unique tool performs semantic analysis of the conversation to find the comments that best summarize the topics people are engaged with as they watch and interact. TMC removes the clutter of check-ins and repeats so your audience stays engaged with both your content and the social media conversation.
MetricsTMC's next layer uses standard metrics such as popularity and language, along with customized blacklisting and whitelisting rules. TMC can be customized for each client to include additional metrics and
interestingness filterssuch as geolocation data, sentiment analysis, social graph data, and metrics provided by third party APIs.
Anti-RedundancySocial media comments are dependent on the context of the social conversation they are part of. TMC considers how similar a comment is to the comments that have already been shown when choosing the next optimal comment to display.
Similarcomments are considered less interesting than unique ones, ensuring that the comments in your stream are varied, different and interesting.
The TMC returns your social engagement team to more important stuff, like actual engagement.
With the TMC, you can set it and forget it, or go play whenever you want. The automated functions are easy to set up and fast to adjust. Forget about conversational clutter and reducing noise. The stream is smooth, evenly paced and delivers the rich content everyone wants to see, and what you want to make sure they see... or not.