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Tracking Sentiment from Day 1 of Defrag

November 12th, 2009 | No Comments | Posted in Blog

Language Computer has been tracking what Twitter users are saying about the first day of Defrag 2009 using Positively, our sentiment extraction tool.

The Good

Here are the top 8 topics people are positive about (ranked in order of how strongly people are feeling).

1. People: So happy,  favorite,  fun,  great,  incredibly interesting,  interesting,  really nice,  smart,  super smart,  way more interesting

2. Day: good,  great,  lovely,  really fun

3. Dinner: Awesome,  Excellent,  absolutely delightful,  lovely

4. Topics: good,  positive

5. Discussions: Liking,  interesting,  lively

6. Talks: interesting,  really interesting,  visually engaging

7. Wifi: as good as the weather,  enjoying,  hella sweet

8.  EventVue, livestream, backchannel: Really enjoying, nice

(Ranking was determined on the inherent expected strength of the sentiment (e.g. hella sweet >> okay) and the number of tweets we found which expressed the same sentiment.  We’ve only listed the unique sentiments up above.)

The Bad

Far fewer negative sentiments.  In most cases, we couldn’t find something that three people were griping about.  Here are the two that reached that threshold:

1.  Kessler’s talk:  dangerous, doesn’t care, stupid, bad, provocative, pointless, useless

2.  language on stage: offended, unnecessary, pointless

The Day 1 “Winners”

After Day1, here are the most positively regarded Twitterers using the #defrag or #defragcon hashtags:  @bpm140, @stoweboyd, @sacca, @benkepes

The Overall Score

So far, tweets are running 88% positive overall for Defrag 2009 after day 1.

defragSenti

Want more info on sentiment tracking on Twitter using Positively?  Contact me at andy@languagecomputer.com.

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More than a Feeling

September 24th, 2009 | 3 Comments | Posted in Blog

Really tickled with all of the much-deserved positive press that 80Legs has attracted after yesterday’s successful public launch at the DEMO09 conference.  (See here, here, and here.  And here.  And here.)  We couldn’t be happier for Shion and Brad and the rest of the 80Legs team.  They’ve got a great product, and they’re well-positioned to really dominate the crawling market.  (Oh, and they’re from Texas Rice, which is a good thing in my book.)  Congrats, guys!

Over the next couple of weeks, I’ll be talking a lot about the different kinds of semantic apps that Swingly (and its parent company, Language Computer) have built to run on the 80Legs platform. We’re psyched about combining Swingly’s broad-coverage semantic apps with the massive amounts of data that 80Legs provides.   It’s a pretty unbeatable combination:  80Legs helps you cast a broad net, while Swingly lets you know exactly what you caught.

While I don’t want to steal any of the 80Legs spotlight, I couldn’t resist telling you a little about the Swingly sentiment analysis app (code name:  Positively) that Shion used during his DEMO pitch yesterday.

Like a lot of other sentiment analysis services (such as those provided by ScoutLabs, Jodange, Evri, NStein, or Crimson Hexagon — just to name a few), Positively was designed to help users discover what people think about pretty much any person, product, organization, or service imaginable.

Want to know what people think about the Neill Blomkamp flick, District 9?  Lots of sentiment analysis apps can boil down an Internet’s worth of noise to a summary score like this:

district9Summary

and a list of comments (usually tagged as positive or negative ) like this:

  • The movie looks great to begin with and this trailer re-enforces we’ll likely get a solid, if not great film out of it. [1]
  • “District 9″ seems an oddly misguided sci-fi movie. [2]
  • It definitely has the goods: an interesting concept, Blomkamp’s clever filmmaking (the movie begins as a faux-documentary and gradually shifts into a survival tale) and ambitions that far exceed the Hollywood norm.[3]

Positively is different from most sentiment analysis apps in two ways.

First, unlike many other services which rely on large amounts of preprocessed data, Positively runs “live” as part of an 80Legs crawl.  Instead of indexing data after it’s become stale, Positively analyzes the sentiments in pages as they’re downloaded.  No indexing, no large-scale distributed processing.  No headaches.  Oh, and you can’t get fresher semantic content.

Second, Positively knows that sometimes you need more than a number.   As it crawls, Positively automatically discovers attributes associated with each of the people, products, or services it’s investigating — and then figures out what people think about each of those attributes.  Interested in District 9?  You might be interested in its:

  • plot
  • actors
  • humor
  • cameos
  • visual effects

Want to track down information on AT&T cell phones?  You might want to know about their:

  • battery life
  • reception
  • chargers
  • apps
  • features
  • size
  • display

No, these attributes don’t come from some big, pre-cooked list of things that might (or might not) be relevant for each product category.   In order to discover why people feel the way they do, Positively hunts for each of the attributes associated with an item — and then discovers what people actually think about that attribute.  Here are a couple of  examples for District 9:

d92

Despite its successful launch yesterday, Positively won’t be available to the general public until 80Legs goes live with its App Store later this Fall.  We are, however, giving sneak peaks.  Want one?  Email me at andy@swingly.com.

Oh, and there’s Boston after the jump!

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