HOT TOPICS: Customer Experience Marketing Automation Social Business SharePoint 2013 Document Management Big Data Mobile DAM

Searching for Deeper Meaning in Sentiment Analysis at #SAS12

Today, several market analysts, community managers, academics and statisticians interested in gleaning as much insight as they can from opinions and attitudes in social media, news and enterprise feedback gathered in New York for the Sentiment Symposium 2012.

Sentiment, Subjectivity, Sense

With the advent of social media, there is so much information being spread about that doesn’t get picked up by traditional customer research and methods. People are talking about your brand, company, products and services in ways that are different and unabashed from what they would say in focus groups and online surveys. When users are on social media, their behavior is much more candid and real, because they are talking about it as it happens.

Symposium morning sessions aimed to present multiple industry perspectives from retail to financial services to news media, all of which are able to mine and measure sentiments with the intent of influencing the market. 

Sentiment

For as many comprehensive analytics tools and solutions there are to help companies dig deeper within their user communities, there are a considerable amount of free tools that can be used to mine data similarly on a much smaller scale. However, as technologies evolve, so does the depth at which you can use basic data to analyze results.

For those who may dismiss social media as an outlet for determining what's hot and what's not, chances are you're not in tune to what people are saying about your brand. But if you're relying solely on Google alerts or Twitter searches to keep you up to date, you're missing the point — and a lot of sentiment. Looking for mentions of product names is only part of the puzzle — being able to effectively understand the emotions associated with it can help you meet customer needs much better, while avoiding product pitfalls. 

Subjectivity

Thomson Reuters, for instance, regularly analyzes new feeds to produce metrics for expected market impact of stocks. By compiling sentiment, headlines, frequency of mentions, as well as how far into articles the stock or company is mentioned, machine-driven data analysis can indicate impact accurately. While this may make for a cool party trick, within the news media and financial world it’s a significant asset to help them navigate copious amounts of data (otherwise known as Big Data) effectively and efficiently. However, this isn’t to say that by simply following Tweets about the stock market will turn you into a Wall Street savant. Rather, it’s about being able to identify behavioral and crowd-based models to explain cyclical booms and busts, as well as sorting trusted news sources from the charlatans. 

Sense

While there is much science and statistics that go into sentiment analysis, much of the decisions and data being used is really dependent on the behaviors of individuals and the environmental factors that impact them. Stuck in traffic? Late for work? Fighting with your spouse? What stock you pick to invest in or the policy decisions you make may be more aggressive than conservative and as such will influence trends in one way or another.

As the day continues at Sentiment Analytics Symposium 2012, we'll be exploring more about the role of emotion in consumer behaviors and how we can turn measurable social insights into business results. 

 
 
 
Useful article?
  Email It      

Tags: , , , , , , , , , , , ,
 
 

Resources

 

Featured Events  View All Events | Add Your Event | feed Events RSS