Purpose and Problems: Sentiment Analysis (Part 2 of 5)

Opinions abound in tweets, wall posts, blog comments and documents on other web and social media platforms. We looked at the text elements of these documents that comprise opinions in the first post in this series.Today, informed by the discussions and presentations at the recent Sentiment Analysis Symposium, let’s examine the business case for sentiment analysis, as well as some issues related to the discovery and analysis processes applied to those documents to mine actionable information for businesses.

Opinions abound in tweets, wall posts, blog comments and documents on other web and social media platforms. We looked at the text elements of these documents that comprise opinions in the first post in this series.

Today, informed by the discussions and presentations at the recent Sentiment Analysis Symposium, let’s examine the business case for sentiment analysis, as well as some issues related to the discovery and analysis processes applied to those documents to mine actionable information for businesses.

Steve Rappaport, ARF Knowledge Solutions Director and author of the just-published Listen First, kicked off the symposium’s Visionary Panel asking why businesses should be using sentiment analysis.

Karla Wachter of communications firm Waggener Edstrom warned that, “Sentiment analysis done in isolation is less likely to solve business problems.” Israel Mirsky of PR firm Porter Novelli expressed that opinion analysis may better describe what businesses seek. They are looking for more than plus, minus and neutral — businesses want to know why and with a high degree of granularity.

Sentiment analysis must have relevance to your business, affirmed Katie Delahaye Paine of research and consulting company KDPaine & Partners, “Show me the data that evidences a certain level of positive sentiment yields sales or translates to purchase intent,” she challenged. “The best uses have to do with business, not with marketing.”

The role of automation

Much of the discussion centered on machine versus human sentiment analysis. Jeff Catlin of text analytics engine developer Lexalytics cited the requirement for machines — the enormous amount of data and the speed at which businesses demand information simply cannot be processed by humans. Catlin acknowledged many limitations, such as handling cynicism and sarcasm. One of the areas he sees machine sentiment analysis as improving is extracting edge cases of value for data triage.

While there has been much innovation, Wachter noted, humans are always going to be required. Mirsky observed that the kinds of data being sought, such as indicators of intent, and decisions attempting to made with sentiment analysis are getting more complex. He felt these would remain difficult to accomplish without use of humans until we have stronger artificial intelligence.

“The engines do well on very concrete information,” Catlin commented, “They are not so good on the squirrelly stuff that humans are apt to say.” He warned that the more measures sought, the more machines are asked to act human, increasing the risk of errors.

When the panel was asked to assess how sentiment analysis may be improved, Mirsky called for better feedback loops — users need to have a better understanding of what’s working. Paine supported Wachter’s statement that context of sentiment is essential for analysis by noting that her firm has clients for whom neutral sentiment is a desirable outcome.

In her later presentation, Fiona McNeill of SAS noted that sentiment analysis does not need to do what current business tools and systems do, but does need to integrate with them. “Sentiment is not always impactful to an organization — nor its cousins of emotion, trust, feelings, and alike,” McNeill wrote on her blog, The Text Frontier, after the symposium. “How someone feels does not always affect what they do – but when it has an important impact, it is worthwhile to analyze it.” In this post, she also presents a sentiment analysis framework built on data validation, learning and changing behavior.

Multiple perspectives

Some of the presentations from the Sentiment Analysis Symposium can be found on the event website — look for presentation links next to the listings. In addition, there were a number of excellent blog posts subsequent to the symposium.