[Air-L] emotion detection machine?

[Charles M. Ess]

Dear colleagues,

One of our students is wanting to analyze emotional content in in the 
comment fields of a major newspaper vis-a-vis specific hot-button issues.

She has a good tool (I think) for scrapping the data - but she is 
stymied over the choice of an emotion analysis tool. She has looked at 
Senpy (http://senpy.gsi.upm.es/#test) and  Twinword 
<https://www.twinword.com/api/emotion-analysis.php> - the latter seems 
the most accurate, but it is also expensive.
She has recently discovered DepecheMood emotion lexicons (Staiano, J., & 
Guerini, M. (2014). Depechemood: a lexicon for emotion analysis from 
crowd-annotated news. arXiv preprint arXiv:1405.1605.) - but this 
suffers from a lack of clarity in terms of explaining its emotional 
categories: awe, indifference, sad, amusement , annoyance, joy, fear and 
anger.

For my part, I am entirely clueless.  Any suggestions that she might 
pursue would be greatly appreciated.

best,
- charles ess
-- 
Professor in Media Studies
Department of Media and Communication
University of Oslo
<http://www.hf.uio.no/imk/english/people/aca/charlees/index.html>

Postboks 1093
Blindern 0317
Oslo, Norway
c.m.ess at media.uio.no