[Air-L] emotion detection machine?

[Jill Walker Rettberg]

Dear Charles,

I'm not an expert, but I think she should be talking with linguists - and I think that what she's looking for is typically called sentiment analysis, not emotion analysis. There are probably tools for social media marketing that might be more readily accessible, but probably less scientifically transparent.
https://en.wikipedia.org/wiki/Sentiment_analysis

Jill

Air-L på vegne av Charles M. Ess <air-l-bounces at listserv.aoir.org på vegne av c.m.ess at media.uio.no> skrev følgende den 05.09.2019, 12:53:

    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
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