Sentiment Analysis: Hypercorps Need Emotion Chips

Sentiment analysis is a relatively new field that is heating up, thanks to the fascination that big companies have with how we feel about them.

The basic idea is that we betray our feelings as we chat to each other in social media like Twitter and Facebook. Consultants like Newssift download the chatter and then analyze it, and present corporations with graphs like the one below. Is positive sentiment toward your hypercorp waxing or waning? Here are the hard numbers presented to big retailers.


(Sentiment trends for large retailers)

So how does sentiment analysis work?

The simplest algorithms work by scanning keywords to categorize a statement as positive or negative, based on a simple binary analysis (“love” is good, “hate” is bad). But that approach fails to capture the subtleties that bring human language to life: irony, sarcasm, slang and other idiomatic expressions. Reliable sentiment analysis requires parsing many linguistic shades of gray...

“We are dealing with sentiment that can be expressed in subtle ways,” said Bo Pang, a researcher at Yahoo who co-wrote “Opinion Mining and Sentiment Analysis,” one of the first academic books on sentiment analysis.

To get at the true intent of a statement, Ms. Pang developed software that looks at several different filters, including polarity (is the statement positive or negative?), intensity (what is the degree of emotion being expressed?) and subjectivity (how partial or impartial is the source?).

(I'm fascinated by the idea that an entirely new science of computer analysis is needed to find out how we consumers feel about companies that promise one thing and deliver another.

Large corporations (or hypercorps, to use John Brunner's word for them from The Shockwave Rider) could easily find out specific facts about their services that consumers do not like. For example, AT&T can read a variety of factual criticisms about their iPhone service in a number of recent tech site blog posts.

However, it is costly to track actual problems with services, and then fix them. Hypercorps like AT&T spend billions honing their brand images, which is just a phrase referring to how we feel about them. If they can track how we feel about them, and then fix how we feel, then the problem is solved.

The service may still suck, but as long as customers don't feel like leaving, it's just as good as actually providing a good service, and much cheaper.)

Anyway, the idea that computer systems might one day learn to interpret the vagaries of human feelings has a long history in science fiction. I'm sure that there are a lot of people who remember that Star Trek: The Next Generation's Commander Data made use of an emotion chip to actually feel emotions himself, which helped him understand his human coworkers and friends.


(Geordi and Data regard the emotion chp)

(Apparently, I'm not yet finished with my feelings about AT&T. Instead of using sentiment analysis to understand how consumers feel about paying 20 bucks per month for the EDGE network, which doles out web pages like Ebenezer Scrooge hands out lumps of coal, AT&T execs could just try using it themselves and then they could feel what we feel directly.)

If you'd like to read an informative article about sentiment analysis that is free from parenthetical ranting, visit NYTimes.com, and you might sift through the informative blog posts on Newssift.

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