acl 2014 论文列表Proceedings of the 5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA@ACL 2014, June 27, 2014, Baltimore, Maryland, USA. |
A Conceptual Framework for Inferring Implicatures.
The Use of Text Similarity and Sentiment Analysis to Examine Rationales in the Large-Scale Online Deliberations.
A cognitive study of subjectivity extraction in sentiment annotation.
Effect of Using Regression on Class Confidence Scores in Sentiment Analysis of Twitter Data.
Sentiment Classification on Polarity Reviews: An Empirical Study Using Rating-based Features.
Evaluating Sentiment Analysis Evaluation: A Case Study in Securities Trading.
Dive deeper: Deep Semantics for Sentiment Analysis.
Lexical Acquisition for Opinion Inference: A Sense-Level Lexicon of Benefactive and Malefactive Events.
Improving Agreement and Disagreement Identification in Online Discussions with A Socially-Tuned Sentiment Lexicon.
Sentiment classification of online political discussions: a comparison of a word-based and dependency-based method.
Opinion Mining and Topic Categorization with Novel Term Weighting.
Credibility Adjusted Term Frequency: A Supervised Term Weighting Scheme for Sentiment Analysis and Text Classification.
Linguistically Informed Tweet Categorization for Online Reputation Management.
Two-Step Model for Sentiment Lexicon Extraction from Twitter Streams.
Challenges in Creating a Multilingual Sentiment Analysis Application for Social Media Mining.
Emotive or Non-emotive: That is The Question.
Modelling Sarcasm in Twitter, a Novel Approach.
An Impact Analysis of Features in a Classification Approach to Irony Detection in Product Reviews.
Semantic Role Labeling of Emotions in Tweets.
Linguistic Models of Deceptive Opinion Spam.
Aspect-Level Sentiment Analysis in Czech.
Inducing Domain-specific Noun Polarity Guided by Domain-independent Polarity Preferences of Adjectives.
An Investigation for Implicatures in Chinese : Implicatures in Chinese and in English are similar !
Robust Cross-Domain Sentiment Analysis for Low-Resource Languages.
Words: Evaluative, Emotional, Colourful, Musical!