[Air-L] emotion detection machine?

[Wiebke Reile]

Dear Charles, 
There are many social listening tools on the corporate level: crimson hexagon and infegy which are media industry research methods for determining sentiment. 
What’s most important is making sure that you have a keyword set that is accurately parsing through the social media posts for sentiment. What’s always difficult is having a lexicon for local terms and also have a method for determining ambiguous posts where the person may mean something different then the keyword that is recognized. 

Best Wiebke 

Wiebke Reile, Ph.D. 
University of Hawai'i at Mānoa
Communication and Information Sciences

Adjunct Lecturer 
Brooklyn College 
Department of Television and Radio 
Wiebke.Reile at brooklyn.cuny.edu

Online Adjunct 
Grand Canyon University 
College of Fine Arts and Production
Wiebke.Reile at my.gcu.edu  

> On Sep 5, 2019, at 7:47 AM, Stuart Shulman <stuart.shulman at gmail.com> wrote:
> 
> Some tools for this work are born in academic research labs instead of
> corporate meeting rooms. For more than a decade we have offered free and
> commercial web-based tools for content labeling and annotator measurement
> in an academic research setting. To date there are 400+ interdisciplinary
> and multilingual citations:
> 
> https://discovertext.com/2018/03/31/scholarly-citations-of-the-coding-analysis-toolkit/
> 
> https://discovertext.com/publications/
> 
> Free demos:
> https://calendly.com/discovertext
> 
> ~Stu
> 
> *Stu Shulman* <https://twitter.com/StuartWShulman>U.S. Soccer
> Federation C-Licensed Coach
> Valeo FC & Capacidad <http://capacidadprograms.org/?page_id=13> Volunteer Coach
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> *Contact Coach Stu about fall 2019 volunteer efforts.
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> 
> 
> 
> 
> 
> On Thu, Sep 5, 2019 at 7:25 AM Jill Walker Rettberg <
> Jill.Walker.Rettberg at uib.no> wrote:
> 
>> 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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