How do we at BrandProtect deal with Social Media Monitoring?
Posted by Elias Vamvakas on Fri, Sep 25, 2009
Part 2 - Continued from....Understanding Social Media Discussion. Why are we getting inundated with Garbage?
Now that we understand the magnitude of the problem, let me tell you how we have dealt with it. Actually, let me tell you how we have transitioned over time to deal with what we have learned and where we think it's going.
Having understood early on that clients are looking for quality not quantity, we designed a process years ago that tried to be all-encompassing when receiving data, but only presented the nuggets of insight that we identified for our clients. In this process, we leveraged technologies and used human tagging and analysis to confirm sentiment and identify issues that we believed our clients cared about.
This is a real example of the process and the magnitude of the effort required to put together target reports.
While our technology did a significant amount of "distilling" the data continued to be overwhelming and the insights were only discovered through our human taggers and analysts. This process while achieving good results and satisfied clients had 2 limitations. The first being costs. Human tagging is obviously expensive and fairly slow. The most important limitation was that the human analysis was limited to the knowledge and experience of the individual doing the tagging. This process was deficient in that it was missing the industry and company knowledge that is embedded within the client.
Therefore, in recent research and development of our new process, we determined the following to be key elements:
- 1- Data had to be relevant and accurately classified for sentiment and Influence
- 2- The methodology had to identify "valuable data". (We define valuable data as discussion threads that when combined with Industry expertise or specific company knowledge will produce actionable insights)
- 3- The technology had to grow and improve over time with the injection of human insight. We wanted a system that would be able to increase in accuracy as data about the industry, the company, lingo, mannerisms and phraseology were identified.
Let me spend a couple of minutes on the importance of word taxonomy, so that you can understand this concept a little better.
If you are trying to analyze a stock whose performance is being criticized as "bad" or the CEO as "wicked", you would want to attribute a different sentiment class than if you were analyzing the performance of the latest rock star and their music among a teenage audience. That's an easy example, but it gets more complicated. If you are in the financial services sector and assessing sentiment of an insurance company you would need to know that "low" is negative if it is referring to earnings, but positive if they are referring to premium rate.
To accomplish the above 3 elements we have now designed our system to go through 5 distinct phases of analysis -
We were very excited about the process, the technology as a base platform, and the results. The platform worked incredibly well with targeted studies, however the results were not as good as we had hoped for undirected studies, something like "show me everything that people talk about us that I should be concerned with" .
I think you will find the "why?" fascinating. I will also go through some real life data and our research to demonstrate our findings, but first let me describe what we have discovered.
Stay tuned for the final part of the Blog - Social Media Monitoring is Complicated....