I think there is a role for automated sentiment within social media monitoring given the amount of data/conversations that need to be tracked and reviewed. It’s important to remember that it’s still early days for sentiment technology so its reliability and accurateness will improve over time.

At the same time, social media monitoring services should still offer the ability for human editing. Within Sysomos’ MAP service, for example, users can manually adjust sentiment settings.

Mark

(I’m the director of communications with Sysomos.com)

Actually, my point in using the mood ring metaphor is to say that sentiment is more interested as a filter than as a standalone metric. Watching the sentiment line go up and down is like watching a mood ring change color–interesting, but lacking in depth.

http://net-savvy.com/executive/measurement/sentiment-analysis-is-not-a-mood-ring.html

I mostly wanted to address what you say in #1 re: vendors not disclosing if their analysis is at a topic or article level. I can’t speak for other vendors, but at Biz360, we do both, and our accuracy is slightly higher at a topic (aka entity) level analysis. I also think that if you are a brand, topic-level analysis is a lot more useful, because there are more articles that deal with several brands at the same time. Our topic level accuracy is 65%, while 62% accuracy at article level (we have 4 sentiments BTW vs. some other vendors’ 3). We trained our data via Mechanical Turk until incremental increase in accuracy was <1%. Users have a chance to override sentiment, as well as toss an article or a source altogether from your results.

Automated sentiment is useful when you have 50,000 articles – you will never be able to read them all! If you want sentiment of an individual article – well, you should probably read it

Cheers!

@themaria @biz360

It’s an interesting metaphor (although I had to resort to Wikipedia to find out what a mood ring is ).

I frame the issue slightly differently. Human sentiment analysis is a very established part of traditional media content analysis (around since the 70s / 80s). This is what many customers – particularly the ones with a PR / comms background – think they are getting: an automated; cheap; effective substitute for expensive human content analysis.

But as you guys know, it’s not the same thing at all – automated sentiment analysis was developed to do something different, follows a different logic path and produces very different results.

Best,
Michelle @Synthesio

This post was mentioned on Twitter by christhomasuk: Just posted: Why automated sentiment analysis shouldn’t feature in social media monitoring tools (http://bit.ly/aNYDdv)…