Is it possible to guess a user's mood based on the structure of text?

Question

I assume a natural language processor would need to be used to parse the text itself, but what suggestions do you have for an algorithm to detect a user\'s mood based on tex

Answer 1

No doubt it is possible to judge a user's mood based on the text they type but it would be no trivial thing. Things that I can think of:

• Capitals tends to signify agitation, annoyance or frustration and is certainly an emotional response but then again some newbies do that because they don't realize the significance so you couldn't assume that without looking at what else they've written (to make sure its not all in caps);
• Capitals are really just one form of emphasis. Others are use of certain aggressive colours (eg red) or use of bold or larger fonts;
• Some people make more spelling and grammar mistakes and typos when they're highly emotional;
• Scanning for emoticons could give you a very clear picture of what the user is feeling but again something like :) could be interpreted as happy, "I told you so" or even have a sarcastic meaning;
• Use of expletives tends to have a clear meaning but again its not clearcut. Colloquial speech by many people will routinely contain certain four letter words. For some other people, they might not even say "hell", saying "heck" instead so any expletive (even "sucks") is significant;
• Groups of punctuation marks (like @#$@$@) tend to be replaced for expletives in a context when expletives aren't necessarily appropriate, so thats less likely to be colloquial;
• Exclamation marks can indicate surprise, shock or exasperation.

You might want to look at Advances in written text analysis or even Determining Mood for a Blog by Combining Multiple Sources of Evidence.

Lastly it's worth noting that written text is usually perceived to be more negative than it actually is. This is a common problem with email communication in companies, just as one example.