| 2 |
Twitter as a Comparable Corpus to build Multilingual Affective Lexicons
|
|
|
|
In: The 7th Workshop on Building and Using Comparable Corpora Proceedings ; The 7th Workshop on Building and Using Comparable Corpora ; https://hal.archives-ouvertes.fr/hal-01615963 ; The 7th Workshop on Building and Using Comparable Corpora, May 2014, Reykjavik, Iceland. pp.17-21 ; https://comparable.limsi.fr/bucc2014/ (2014)
|
|
BASE
|
|
Show details
|
|
|
| 3 |
Toward a unifying model for Opinion, Sentiment and Emotion information extraction
|
|
|
|
In: The 9th International Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-01613403 ; The 9th International Conference on Language Resources and Evaluation, May 2014, Reykjavik, Iceland. pp.3881-3886 ; http://www.lrec-conf.org/proceedings/lrec2014/index.html (2014)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
DCU: aspect-based polarity classification for SemEval task 4
|
|
|
|
In: Wagner, Joachim orcid:0000-0002-8290-3849 , Arora, Piyush orcid:0000-0002-4261-2860 , Cortes, Santiago, Barman, Utsab, Bogdanova, Dasha, Foster, Jennifer orcid:0000-0002-7789-4853 and Tounsi, Lamia (2014) DCU: aspect-based polarity classification for SemEval task 4. In: International Workshop on Semantic Evaluation (SemEval-2014), 23-24 Aug 2014, Dublin, Ireland. ISBN 978-1-941643-24-2 (2014)
|
|
BASE
|
|
Show details
|
|
|
| 5 |
TriVis: visualising multivariate data from sentiment analysis
|
|
|
|
In: Doyle, Maryanne, Smeaton, Alan F. orcid:0000-0003-1028-8389 and Bermingham, Adam (2014) TriVis: visualising multivariate data from sentiment analysis. In: 8th Annual Irish Human Computer Interaction (iHCI) conference, 1-2 Sept 2014, DCU, Dublin, Ireland. (2014)
|
|
BASE
|
|
Show details
|
|
|
| 6 |
Overview of the Evalita 2014 SENTIment POLarity Classification Task
|
|
|
|
In: Proceedings of the 4th evaluation campaign of Natural Language Processing and Speech tools for Italian (EVALITA'14) ; https://hal.inria.fr/hal-01228925 ; Proceedings of the 4th evaluation campaign of Natural Language Processing and Speech tools for Italian (EVALITA'14), 2014, Pisa, Italy. ⟨10.12871/clicit201429⟩ (2014)
|
|
BASE
|
|
Show details
|
|
|
| 7 |
Overview of the Evalita 2014 SENTIment POLarity Classification Task
|
|
|
|
In: Proceedings of the 4th evaluation campaign of Natural Language Processing and Speech tools for Italian (EVALITA'14) ; https://hal.inria.fr/hal-01195786 ; Proceedings of the 4th evaluation campaign of Natural Language Processing and Speech tools for Italian (EVALITA'14), Dec 2014, Pisa, France. ⟨10.12871/clicit201429⟩ (2014)
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Annals of A Model to Compute Degree of Polarity of Review Titles
|
|
|
|
In: http://www.researchmathsci.org/apamart/apam-v7n1-11.pdf (2014)
|
|
BASE
|
|
Show details
|
|
|
| 9 |
JOINT_FORCES : unite competing sentiment classifiers with random forest ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 10 |
Supervised and semi-supervised statistical models for word-based sentiment analysis ... : Überwachte und halbüberwachte statistische Modelle zur wortbasierten Sentimentanalyse ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 11 |
Assigning Polarity Automatically to the Synsets of a Wordnet-like Resource
|
|
Gomes, Paulo. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2014. : OASIcs - OpenAccess Series in Informatics. 3rd Symposium on Languages, Applications and Technologies, 2014
|
|
BASE
|
|
Show details
|
|
|
| 13 |
FREQUENCY AND FACT: LEARNING ABOUT THE WORLD THROUGH A CORPUS OF WORLD-ENGLISHES
|
|
|
|
BASE
|
|
Show details
|
|
|
| 14 |
Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features
|
|
|
|
BASE
|
|
Show details
|
|
|
| 15 |
VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text
|
|
|
|
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)
|
|
Abstract:
The inherent nature of social media content poses serious challenges to practical applications of sentiment analysis. We present VADER, a simple rule-based model for general sentiment analysis, and compare its effectiveness to eleven typical state-of-practice benchmarks including LIWC, ANEW, the General Inquirer, SentiWordNet, and machine learning oriented techniques relying on Naive Bayes, Maximum Entropy, and Support Vector Machine (SVM) algorithms. Using a combination of qualitative and quantitative methods, we first construct and empirically validate a gold-standard list of lexical features (along with their associated sentiment intensity measures) which are specifically attuned to sentiment in microblog-like contexts. We then combine these lexical features with consideration for five general rules that embody grammatical and syntactical conventions for expressing and emphasizing sentiment intensity. Interestingly, using our parsimonious rule-based model to assess the sentiment of tweets, we find that VADER outperforms individual human raters (F1 Classification Accuracy = 0.96 and 0.84, respectively), and generalizes more favorably across contexts than any of our benchmarks.
|
|
Keyword:
Human Centered Computing; Sentiment Analysis; Social Media; Validated Sentiment Lexicon
|
|
URL: https://ojs.aaai.org/index.php/ICWSM/article/view/14550
|
|
BASE
|
|
Hide details
|
|
|
| 16 |
The USAGE review corpus for fine-grained, multi-lingual opinion analysis ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 17 |
The USAGE review corpus for fine-grained, multi-lingual opinion analysis ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 18 |
Swiss-chocolate : sentiment detection using sparse SVMs and part-of-speech n-grams ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 19 |
Universal Dimensions of Meaning Derived from Semantic Relations among Words and Senses: Mereological Completeness vs. Ontological Generality
|
|
|
|
In: Computation ; Volume 2 ; Issue 3 ; Pages 61-82 (2014)
|
|
BASE
|
|
Show details
|
|
|
| 20 |
Contextual Sentiment Analysis With Untrained Annotators ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|
|
