Semantic Analytics – Detecting Context within Social Media ConversationsIn many ways, we are at the beginning of social media usage and adoption. Most usage charts and graphs are platform- or country specific. Although, I did find this very interesting social web involvement map in different markets but it’s quite hard to see the breakdown. However, the point I am trying to make is that social media adoption is still in its infancy. When you consider the number of individuals becoming authors, contributors, publishers, sharing and collaborating it might be worth admitting that few of us know where this evolution is going and what the end-state of this phase may look like. But this blog post is not about the importance of understanding social media adoption and technology but rather how to manage all of this new data, that is growing both quickly and daily. One of the bigger challenges organizations face with the explosion of social media and consumer-generated content is the ability to extract, process and leverage contextually relevant data in real-time. It brings to mind a few questions, like:
- What will the social web look like once under-represented locations join the conversation?
- Do you have a strategy for filtering and managing data that is unique to your brand, your products and services and your industry as the source of information grows exponentially?
- How do you intend to identify shifts in the conversation as they merge with other topics, of less or more relevance?
- Have you determined the criteria for when an emerging trend or topic spills over into an entrenched idea?
Today’s Social Media LandscapeHere’s our view of the social media data landscape today, including sources of private data, like: surveys, private communities or call center information. But even we know that this landscape is expanding all the time and our collection may look very different a year from now.
The Search for Truth and MeaningI’m building a little on the ideas described in this previous blog entry, "Semantic analytics serves the truth & vegetables from a social media diet", which emphasized the importance of identifying all on-topic engagements and then uncovering the truth of social media conversations. Identifying all related and on-topic social conversation will require a sophisticated listening platform that in many ways resembles a more traditional search engine than a simple monitoring tool. There are two key functions of an enterprise listening platform:
- Identifying and collecting on-topic conversations
- Applying advanced analytics to surface consumer intentions and preferences, including author information