There are many ways to analyze and measure sentiments expressed online. One of the inherent challenges in attempting to scale the practice, however, is the number of places consumers express their opinions and the resources necessary to sift through millions of words. Twitter and Facebook help narrow that gap somewhat with built-in applications that perform keyword-based sentiment analysis on any topic instantly.
Facebook creatively launched its capability, called Lexicon, with a project called the Gross National Happiness Index. The company's software analyzes every user's status update for a particular day, determining if it was positive or negative, and created a chart for each day of the year. Not surprisingly, the peaks occur on major holidays, while the lowest points are on dates when well-known celebrities die.
Twitter itself doesn't yet offer a sentiment analysis tool, but third-party services aggregate millions of tweets and analyze whether they reflect positively or negatively on a word or phrase. Tweet Feel, Twendz, and Twitter Sentiment are just a few of the sites where users can type in a search term to find out how favorable it is within the Twitter community.
Google has been experimenting with similar technology with its Google Trends service, which doesn't track favorability but does show popularity of search terms over a timeline. Its uses range from the noble (tracking the spread of disease by linking searchers' IP addresses with symptomatic search terms) to the mundane (showing how fast news of a sports injury spreads). During the presidential election, a number of news sources used Google Trends to show which political figures were rising (or falling) in popularity.