Hi Charles, To help with some student projects, I patched together an almost ridiculously primitive tool, using Python's emoji package - you paste text in a form field and get emoji statistics in return: http://labs.polsys.net/tools/textanalysis/ May still be useful somehow. best, Bernhard --- Bernhard Rieder | Associate Professor | New Media and Digital Culture University of Amsterdam | Turfdraagsterpad 9 | 1012 XT Amsterdam | The Netherlands http://thepoliticsofsystems.net | http://labs.polsys.net | https://www.digitalmethods.net | @RiederB
On 11 Jun 2018, at 11:44, Charles M. Ess <c.m.ess@media.uio.no> wrote:
Dear AoIRists,
one of our MA students is exploring the role of diverse emotions - first of all, anger - in responses to news stories on three major Norwegian news sites. The broad hypothesis is that anger will be most prevalent and effective in catalyzing further response (including sharing, likes, etc.) - but four emotions total are taken on board: sadness, anger, surprise, and happiness.
1) There is an online tool available for analyzing the emotive content of texts - "The SATI API enables to perform Sentiment Analysis from Textual Information", etc. Comments and observations on its utility, validity?
2) Recommendations, please, for either useful examples of similar research, especially with a view towards methods of accumulating and then analyzing emoticons, and/or other suggestions regarding possible tools?
Many thanks in advance, - 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@media.uio.no _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org
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