PolarityClassification

We investigate the combination of several sources of information for the purpose of sub- jectivity recognition and polarity classification in meetings. We focus on features from two modalities, transcribed words …...

We describe a novel language-independent ap- proach to the task of determining the polarity, positive or negative, of the author’s opinion on a specific topic in natural language text. In …...

We describe a pattern-based system for polarity classification from texts. Our system is currently restricted to the positive, negative or neutral po- larity of phrases and sentences. It analyses the …...

AbstractIn this paper, we propose GermanPolarityClues, a new publicly available lexical resource for sentiment analysis for the German language. While sentiment analysis and polarity classification has been extensively studied at …...

AbstractSubjectivity analysis and authorship attribution are very popular areas of research. However, work in these two areas has been done separately. We believe that by combining information about subjectivity in …...

AbstractIn recent years, text classification in sentiment analysis has mostly focused on two types of classification, the distinction between objective and subjective text, i.e. subjectivity detection, and the distinction between …...

AbstractThis paper presents Q-WordNet, a lexical resource consisting of WordNet senses automatically annotated by positive and negative polarity. Polarity classification amounts to decide whether a text (sense, sentence, etc.) may …...

Quotations from financial leaders can have significant influence upon the immediate prospects of economic actors. Indiscreet or candid comments from senior business leaders have had detrimental effects upon their organizations. …...

AbstractThis paper presents an approach to construction of an annotated corpus for German political news for the opinion mining task. The annotated corpus has been applied to learn relation extraction …...

AbstractThis paper presents SentiSense, a concept-based affective lexicon. It is intended to be used in sentiment analysis-related tasks, specially in polarity and intensity classification and emotion identification. SentiSense attaches emotional …...

This paper describes the system implemented by Fundaci´o Barcelona Media (FBM) for clas- sifying the polarity of opinion expressions in tweets and SMSs, and which is supported by a UIMA …...

Extensive experiments have validated the ef- fectiveness of the corpus-based method for classifying the word’s sentiment polarity. However, no work is done for comparing d- ifferent corpora in the polarity …...

In this paper, we describe our system for the SemEval-2013 Task 2, Sentiment Analysis in Twitter. We formed features that take into ac- count the context of the expression and …...

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. …...

AbstractIn this paper, we study the problems of opinion expression extraction and expression-level polarity and intensity classification. Traditional fine-grained opinion analysis systems address these problems in isolation and thus cannot …...

This paper proposes an approach to solve message- and phrase-level polarity classi- fication in Twitter, derived from an exist- ing system designed for Spanish. As a first step, an ad-hoc …...

The LT3 system perceives ABSA as a task consisting of three main subtasks, which have to be tackled incrementally, namely aspect term extraction, classification and polarity classification. For the first …...

This paper describes our sentiment classifica- tion system submitted to SemEval-2015 Task 10. In the message-level polarity classifica- tion subtask, we obtain the highest macro- averaged F1-scores on three out …...

This paper describes the polarity classification system designed for participation in SemEval- 2016 Task 5 - ABSA. The aim is to determine the sentiment polarity expressed towards cer- tain aspect …...

This paper presents an alternative approach to polarity and intensity classification of senti- ments in microblogs. In contrast to previous works, which either relied on carefully de- signed hand-crafted feature …...

AbstractThe fine-grained task of automatically detecting all sentiment expressions within a given document and the aspects to which they refer is known as aspect-based sentiment analysis. In this paper we …...

AbstractSentiment shifters, i.e., words and expressions that can affect text polarity, play an important role in opinion mining. However, the limited ability of current automated opinion mining systems to handle …...

AbstractSpanish is the third-most used language on the internet, after English and Chinese, with a total of 7.7% (more than 277 million of users) and a huge internet growth of …...

AbstractThis paper describes the approach we used for SemEval-2017 Task 4: Sentiment Analysis in Twitter. Topic-based (target-dependent) sentiment analysis has become attractive and been used in some applications recently, but …...

The large amount of data available in social media, forums and websites motivates researches in several areas of Natural Language Processing, such as sentiment analysis. The popularity of the area …...

AbstractLexicon based methods for sentiment analysis rely on high quality polarity lexicons. In recent years, automatic methods for inducing lexicons have increased the viability of lexicon based methods for polarity …...