LexaBlog: Our Sentiment about Text Analytics and Social Media

In an earlier post, Jeff Catlin described analysis that we did around Bally's vs. Bellagio using publicly available customer reviews. We did this analysis using something called "categories", which is basically a fancy name for search strings. The important aspect of this analysis was in finding the sentiment associated with different important aspects of the hotel experience - using a known set of categories.

One of the two major new features in Salience 4.3 (releasing around June 30th) is "opinion mining". Opinion mining expands our core technology to handle indirect quotes. We've been able to extract quote-mark delimited quotes for a while now, and you could perform further analysis on those quotes (which were attached to the speaker).

Opinion mining means that Salience 4.3 can now handle sentences like:
1) Seth then asserted that this was a truly awesome feature.
2) Tim agreed that Bill was unduly angry.
3) Paul explained that the code was broken.

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div style="width:425px" id="__ss_4410642">Text analytics workshow 2-modified

The Super Bowl brings inevitable re-running and armchair quarterbacking at all the advertising agencies about how they could have done better.

There's statistics and measurements galore, from Nielsen to USAToday about popularity and viewing.

I was curious about what people were saying about the ads, so, I pointed Lexascope at the blogosphere and news feeds, and below is what it told me.  We didn't do a big scientific-sounding study with lots of important seeming partners, we just snagged a bunch of blog and news content and let Lexascope read it and tell us what's up.