conceptnet for mood/sentiment analysis?

[Robert Decker]

Hi,

We've been investigating divisi2 for mood/sentiment analysis. I
understand that we're on conceptnet4 with the current version of
divisi2?

At this point we've only been doing the simple check of words and
their relation to good and bad concepts.

Next we're going to try the happy<->sad example shown here:
http://csc.media.mit.edu/docs/divisi2/tutorial_category.html

But expand it to multiple vectors, but what is a good strategy for
this? Do we need to come up with words on opposite ends of multiple
sentiment vectors?
(like the happy<->sad example where you set happy=+1 and sad=-1 and
see where your word falls on the scale)

Or should we instead come up with some sentiment concepts and build
related categories from these?
For example:
[anger, loathing, rage]
[fear, uneasiness, trepidation]
[sad, sadness, grief, mourning]
[happy, elated]

Has anyone tried using conceptnet to get mood/sentiment? It seems to
be working but I'm wondering if anyone has any ideas.

thanks.

--
-robert

[Catherine Havasi]

Hi Ben,

But expand it to multiple vectors, but what is a good strategy for
this? Do we need to come up with words on opposite ends of multiple
sentiment vectors?

What works better for this is to create a happy vector and a sad vector.  Then to find documents which are positive, look for things similar to the happy vector MINUS the sad vector.
 

[anger, loathing, rage]
[fear, uneasiness, trepidation]
[sad, sadness, grief, mourning]
[happy, elated]

That works too.  You'll want to use the add/subject technique described above.
 

 

Has anyone tried using conceptnet to get mood/sentiment? It seems to
be working but I'm wondering if anyone has any ideas.

Frequently! It's been used for this in a lot of projects, most notably SenticNet by Erik Cambria and as a small part of the Luminoso project which eventually turned into a company.

- Catherine

 

thanks.

--
-robert

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