mirror of
https://github.com/gsi-upm/senpy
synced 2024-11-24 09:02:28 +00:00
a0abbede49
Update RDFlib to 6.1.1 (removed rdflib-jsonld, as it is deprecated) Bumped minimum python version: 3.7 (as a result of RDFLIB 6) Added ProxyFix to run behind nginx (Added --no-proxy to run without the fix) Replaced http media links to protocol-agnostic links in playground Enable CORS (via --enable-cors) Update old urls (replaced *.cluster.gsi.dit.upm.es with *.gsi.upm.es)
37 lines
1.5 KiB
ReStructuredText
37 lines
1.5 KiB
ReStructuredText
Publications
|
|
============
|
|
|
|
|
|
And if you use Senpy in your research, please cite `Senpy: A Pragmatic Linked Sentiment Analysis Framework <http://gsi.upm.es/index.php/es/investigacion/publicaciones?view=publication&task=show&id=417>`__ (`BibTex <http://gsi.upm.es/index.php/es/investigacion/publicaciones?controller=publications&task=export&format=bibtex&id=417>`__):
|
|
|
|
.. code-block:: text
|
|
|
|
Sánchez-Rada, J. F., Iglesias, C. A., Corcuera, I., & Araque, Ó. (2016, October).
|
|
Senpy: A Pragmatic Linked Sentiment Analysis Framework.
|
|
In Data Science and Advanced Analytics (DSAA),
|
|
2016 IEEE International Conference on (pp. 735-742). IEEE.
|
|
|
|
|
|
Senpy uses Onyx for emotion representation, first introduced in:
|
|
|
|
.. code-block:: text
|
|
|
|
Sánchez-Rada, J. F., & Iglesias, C. A. (2016).
|
|
Onyx: A linked data approach to emotion representation.
|
|
Information Processing & Management, 52(1), 99-114.
|
|
|
|
Senpy uses Marl for sentiment representation, which was presented in:
|
|
|
|
.. code-block:: text
|
|
|
|
Westerski, A., Iglesias Fernandez, C. A., & Tapia Rico, F. (2011).
|
|
Linked opinions: Describing sentiments on the structured web of data.
|
|
|
|
The representation models, formats and challenges are partially covered in a chapter of the book Sentiment Analysis in Social Networks:
|
|
|
|
.. code-block:: text
|
|
|
|
Iglesias, C. A., Sánchez-Rada, J. F., Vulcu, G., & Buitelaar, P. (2017).
|
|
Linked Data Models for Sentiment and Emotion Analysis in Social Networks.
|
|
In Sentiment Analysis in Social Networks (pp. 49-69).
|