All posts tagged sentiment

In last week’s post, I covered a bit on articulating a problem in data mining and feature engineering. This week, we’ll go further into my UW presentation and talk about production systems, with examples in text mining and sentiment. Again, all of this can be seen visually in my SlideShare presentation or, even better, in person next Wednesday at this Seattle Meet-Up >>

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sherlock holmes silhouette in studio on white backgroundExperiencing persistent negative perceptions is not uncommon for a brand. To uncover the reasons for them, companies often look at the landscape of their social research by getting reports of post volume and sentiment.

That type of data only skims the surface of the problem, however. Companies are not diving deep enough with just those raw results. The next step in the detective work is bringing deeper segmentation and analysis to find real business answers.

Deep segmentation of data allows marketers to attack the problem from a specific point of view, getting to the root of what’s causing and driving it, and where and how people are talking about it. Marketers can get better insights from unstructured content, and the only way to do that is by breaking it down to levels beyond just media channel, volume, and sentiment. Therein lies the evolution of social.

Though different ways to approach segmentation exist, this post will focus on three levels of dissection from which a brand can gain huge insight in researching a negative perception problem.

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snowden2One of the more controversial events happening at South by Southwest this year is the talk with Edward Snowden, the infamous NSA whistle-blower. It was announced on March 4th that this talk would occur today, the 10th, remotely from Russia where he’s received asylum, and livestreamed by The Texas Tribune. When the event was announced, volume surrounding the topic peaked at nearly 13k posts across all media types, with nearly 12k of those posts coming from Twitter.

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segmentationWhat are real insights? Let’s answer that question by answering what they aren’t. Real insights aren’t brand-level trendlines, or general metrics, or basic sentiment charts. They are calculated, methodical findings that result from segmentation. What do I mean by segmentation? Think of it this way: Your check engine light comes on in your car. That’s a top-level indicator that should prompt you to open the hood. It’s like a general trendline that shows a particular spike. You have no idea what that spike represents, you just know you should probably investigate. Opening the hood exposes the engine, but unless your car is spewing oil, chances are you’ll need to have further examination done to determine the issue. Data segmentation and true insight gathering follows this exact concept. Each part of the engine represents a segment of data, which must be analyzed further to identify the issue. By doing this, you compartmentalize your analysis, which enables you to identify the issue much more quickly, revealing an action that should be taken. Read more…

On October 16th, we had the opportunity to conduct a webcast with a guest speaker from Ogilvy – SVP Irfan Kamal. A few months back, Ogilvy embarked on a study to try to find out what drives true brand advocacy. Put simply, an advocate is what you want. Satisfied customers have a limited value in comparison.  Advocates will talk positively about your business not only when asked, but whenever they think the information is valuable to others. That advocacy can be amplified by social media in huge ways. The presentation reviewed the drivers of advocacy in four major markets. It was really interesting to see that different things drive advocacy in different markets. I won’t give the secret away here. Check out the webcast. It will give you more great info than I ever could in a blog post.

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The September Fall TV new show rollout is a bit like Christmas. It’s an exciting time when people come together looking forward to merriment, focusing a little less on their diets and dreaming of the wonderful experiences coming their way. In this case, all the exciting new shows that have been heavily promoted by all the networks. However, sometimes the reality of it all is that the experience rarely lives up to all they hype and all you get are terrible memories you can’t erase.

Leading up to September we put together our dream watch lists:

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Yesterday I blogged about the VMA performances heard around the world. Today I am going to focus on what matters most with any award show – Fashion.

Taylor Swift looked beautiful with Great Gatsby-esque hair and many others were lovely or trendy but I really appreciated the throw back styles of a select few. Miley Cyrus seemed inspired by 2009 Gwen Stefani, because 4 years ago can be vintage.


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March madness is one of my favorite events of the year.  As a Big Ten alumni I always hope that my school will make it to the finals and I follow the games closely.  It is also fun to see how these games drive social conversations online.  Between rabid sports fans and passionate alumni, these games create lots of excitement and discussions!

While I have my personal favorites (hint: Michigan and Indiana), we used Visible Intelligence to take a look back at the second round leading to the Sweet Sixteen. We know who won in our basketball brackets, but what about the Twitter tournament? Who was mentioned most and who won the the social hearts and minds of basketball fans?

As you can see in the infographic below, created with ExactTarget, there were winners, losers, cinderella stories and underdogs.


  • In the top two regions, Oregon and Michigan (Go Blue!) are always among the top schools when it comes to social media in college sports
  • Duke and North Carolina are huge rivals with huge fanbases, so it’s no surprise that these two schools are popular on Twitter
  • In the bottom half of the bracket, Gonzaga (the ultimate Cinderella and often fan-favorite) had the most mentions in the west region
  • Marquette (who won on a buzzer-beater) had the most mentions overall

What happens on the court may not always reflect who wins on Twitter.  Teams with large fan bases and active social media accounts did well. Games with high drama and exciting finishes had more mentions. Bring on the Sweet Sixteen and Elite Eight!

March Madness Round 2 Twitter winners

March Madness Round 2 Twitter winners

The Hunger Games

Image via Lionsgate

This previous weekend was notable in Seattle for its glorious weather (some of us might have seriously considered trying to swim in the lake) but I suspect many locals were otherwise engaged–as was the entire country. It was the Hunger Games opening weekend and if you didn’t see the movie I think I can reasonably assume that you know someone who did.

I was free to enjoy the weekend glimpse of sun because I was one of the crazies (fans) in line to see the midnight screening Thursday night. I know the reaction to the film that took place in my theater, but I am no movie reviewer! Let’s leave that to the expert social media masses. Using Visible Intelligence®, I took a look at conversation around the film– whose well documented social media presence has been impressive leading up to the premiere (the advanced screening Twitter contest, elaborate suite of websites, and engaging Facebook page are just the tip of the iceberg) to see what the talking points were. Read more…

Looking at the sentiment of social data can be a very useful way to help get a snapshot view of consumer perceptions, quickly dig into a pile of potential customer servicing opportunities and provide another layer of filtering to identify insights into the complex ways that people discuss and emote about topics.  Sentiment scores are a standard data enrichment piece for enterprise-ready social media and monitoring solutions, and a few free tools offer lightweight, less accurate versions with their functionality.

So as a business, what kind of questions should you keep in mind while evaluating social sentiment solutions when choosing a social listening platform?  Here are 9 questions you should answer for yourself when evaluating what a specific software solution has to offer. Read more…

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