Home
Catalogue search
Refine your search:
Keyword
Creator / Publisher:
Sintsova, Valentina (5)
Pu, Pearl (4)
Musat, Claudiu-Cristian (2)
Kempter, Renato (1)
Musat, Claudiu (1)
Year
Medium:
Online (5)
Type
BLLDB-Access
Search in the Catalogues and Directories
All fields
Title
Creator / Publisher
Keyword
Year
AND
OR
AND NOT
All fields
Title
Creator / Publisher
Keyword
Year
AND
OR
AND NOT
All fields
Title
Creator / Publisher
Keyword
Year
AND
OR
AND NOT
All fields
Title
Creator / Publisher
Keyword
Year
AND
OR
AND NOT
All fields
Title
Creator / Publisher
Keyword
Year
Sort by
creator [A → Z]
'
creator [Z → A]
'
publishing year ↑ (asc)
'
publishing year ↓ (desc)
'
title [A → Z]
'
title [Z → A]
'
Simple Search
Hits 1 – 5 of 5
1
Dystemo: Distant Supervision Method for Multi-Category Emotion Recognition in Tweets
Sintsova, Valentina
;
Pu, Pearl
In: http://infoscience.epfl.ch/record/223235 (2016)
BASE
Show details
2
Advancing Fine-Grained Emotion Recognition in Short Text
Sintsova, Valentina
In: http://infoscience.epfl.ch/record/221615 (2016)
BASE
Show details
3
Semi-Supervised Method for Multi-Category Emotion Recognition in Tweets
Sintsova, Valentina
;
Musat, Claudiu-Cristian
;
Pu, Pearl
In: http://infoscience.epfl.ch/record/210750 (2015)
BASE
Show details
4
EmotionWatch: Visualizing Fine-Grained Emotions in Event-Related Tweets
Kempter, Renato
;
Sintsova, Valentina
;
Musat, Claudiu
...
In: Proceedings of the International AAAI Conference on Web and Social Media; Vol. 8 No. 1 (2014): Eighth International AAAI Conference on Weblogs and Social Media ; 2334-0770 ; 2162-3449 (2014)
BASE
Show details
5
Fine-Grained Emotion Recognition in Olympic Tweets Based on Human Computation
Sintsova, Valentina
;
Musat, Claudiu-Cristian
;
Pu, Pearl
In: http://infoscience.epfl.ch/record/197185 (2014)
Abstract:
In this paper, we detail a method for domain specific, multi-category emotion recognition, based on human computation. We create an Amazon Mechanical Turk1 task that elicits emotion labels and phrase-emotion associations from the participants. Using the proposed method, we create an emotion lexicon, compatible with the 20 emotion categories of the Geneva Emotion Wheel. GEW is the first computational resource that can be used to assign emotion labels with such a high level of granularity. Our emotion annotation method also produced a corpus of emotion labeled sports tweets. We compared the crossvalidated version of the lexicon with existing resources for both the positive/negative and multi-emotion classification problems. We show that the presented domain-targeted lexicon outperforms the existing general purpose ones in both settings. The performance gains are most pronounced for the fine-grained emotion classification, where we achieve an accuracy twice higher than the benchmark.2
URL:
https://infoscience.epfl.ch/record/197185/files/W13-1603.pdf
http://infoscience.epfl.ch/record/197185
BASE
Hide details
Mobile view
All
Catalogues
UB Frankfurt Linguistik
0
IDS Mannheim
0
OLC Linguistik
0
UB Frankfurt Retrokatalog
0
DNB Subject Category Language
0
Institut für Empirische Sprachwissenschaft
0
Leibniz-Centre General Linguistics (ZAS)
0
Bibliographies
BLLDB
0
BDSL
0
IDS Bibliografie zur deutschen Grammatik
0
IDS Bibliografie zur Gesprächsforschung
0
IDS Konnektoren im Deutschen
0
IDS Präpositionen im Deutschen
0
IDS OBELEX meta
0
MPI-SHH Linguistics Collection
0
MPI for Psycholinguistics
0
Linked Open Data catalogues
Annohub
0
Online resources
Link directory
0
Journal directory
0
Database directory
0
Dictionary directory
0
Open access documents
BASE
5
Linguistik-Repository
0
IDS Publikationsserver
0
Online dissertations
0
Language Description Heritage
0
© 2013 - 2024 Lin|gu|is|tik
|
Imprint
|
Privacy Policy
|
Datenschutzeinstellungen ändern