Лексикон настроений

AbstractWe demonstrate a method of improving a seed sentiment lexicon developed on essay data by using a pivot-based paraphrasing system for lexical expansion coupled with sentiment profile enrichment using crowdsourcing. …...

Aspect-based opinion mining has attracted lots of attention today. In this paper, we address the problem of product aspect rat- ing prediction, where we would like to ex- tract the …...

In this paper, we propose to build large-scale sentiment lexicon from Twitter with a representation learning approach. We cast sentiment lexicon learning as a phrase-level sentiment classification task. The challenges …...

The sentiment captured in opinionated text provides interesting and valuable informa- tion for social media services. However, due to the complexity and diversity of linguistic representations, it is challeng- ing …...

This paper describes our systems submitted to the target-dependent sentiment polarity clas- sification subtask in aspect based sentimen- t analysis (ABSA) task (i.e., Task 12) in Se- mEval 2015. To …...

This paper presents the approach of the GTI Research Group to SemEval-2016 task 4 on Sentiment Analysis in Twitter, or more specif- ically, subtasks A (Message Polarity Classifi- cation), B …...

AbstractThis paper presents NileULex, which is an Arabic sentiment lexicon containing close to six thousands Arabic words and compound phrases. Forty five percent of the terms and expressions in the …...

AbstractThis report describes our participation to SemEval-2017 Task 4: Sentiment Analysis in Twitter, specifically in subtasks A, B, and C. The approach for text sentiment classification is based on a …...

AbstractPrevious studies have shown that investor sentiment indicators can predict stock market change. A domain-specific sentiment lexicon and sentiment-oriented word embedding model would help the sentiment analysis in financial domain …...

AbstractSentiment lexicon is an important tool for identifying the sentiment polarity of words and texts. How to automatically construct sentiment lexicons has become a research topic in the field of …...

AbstractAlthough many sentiment lexicons in different languages exist, most are not comprehensive. In a recent sentiment analysis application, we used a large Chinese sentiment lexicon and found that it missed …...

AbstractAttention mechanisms have been leveraged for sentiment classification tasks because not all words have the same importance. However, most existing attention models did not take full advantage of sentiment lexicons, …...

In this paper we present a novel approach to the construction of an extensive, sense-level sentiment lexicon built on the basis of a wordnet. The main aim of this work …...

AbstractThis paper describes our submissions to SemEval 2018 task 1. The task is affect intensity prediction in tweets, including five subtasks. We participated in all subtasks of English tweets. We …...

The paper describes an automatic Twitter sentiment lexicon creator and a lexicon-based sentiment analysis system. The lexicon creator is based on a Pointwise Mutual Information approach, utilizing 6.25 million automatically …...

AbstractWhen assigning quantitative labels to a dataset, different methodologies may rely on different scales. In particular, when assigning polarities to words in a sentiment lexicon, annotators may use binary, categorical, …...

AbstractSentiment analysis is an area of substantial relevance both in industry and in academia, including for instance in social studies. Although supervised learning algorithms have advanced considerably in recent years, …...

Sentiment lexicons are instrumental for senti- ment analysis. One can use a set of sentiment words provided in a sentiment lexicon and a lexicon-based classifier to perform sentiment analysis. One …...