- Sarcasm: is one of the most difficult sentiments for automated tracking to interpret properly. Example: “It was awesome for the week that it worked.”
- Navel gazing: is when social media tracking turns up items related to your own promotional efforts, and should be filtered out.
- Neutral sentiment: is similar to the concept of swing voters, and Frank recommended dividing it into specific themes to uncover more detailed opinions.
- Relative sentiment: is not a classic negative, but can be a negative nonetheless. Example: “I bought an iPhone” is good for Apple, but not for Nokia.
- Compound or multidimensional sentiment: contain positives and negatives in the same phrase. Example: “I love Mad Men, but hate the misleading episode trailers.”
- Conditional sentiment: includes actions that may happen in the future. Example: the customer isn’t angry now but says he will be if the company doesn’t call him back.
- Positive feelings can be unrelated to the core issue. For example, many comments about actors focus on their personal lives, not their acting skills.
- Negative sentiment is not necessarily bad: This relates to the classic PR dilemma regarding negative publicity. Example: Sarah Palin’s appearance on the Today show generated many negative comments but still drove ratings increases.
- Ambiguous negative words: Their context needs to be thoroughly understood and tagged accordingly. Example: “That backflip was so sick” is really a positive statement.
The Wall Street Journal’s weekend Review section uses NetBase data to track Twitter and Facebook sentiment around timely topics. (see image above) Last week, they analyzed the public’s reaction to the recent high sale price for the famous Munch painting, “The Scream.” While the sale price prompted mixed views, the extreme sentiment expressed in the painting itself was universal.