AbstractThis paper presents our research in detection of emotive (emotionally loaded) sentences. The task is defined as a text classification problem with an assumption that emotive sentences stand out both lexically and grammatically. The assumption is verified exper- imentally. The experiment is based on n-grams as well as more sophisticated patterns with disjointed elements. To deal with the sophisticated patterns a novel language modelling algorithm based on the idea of language combinatorics is applied. The results of experiments are explained with the standard means of Precision, Recall and balanced F-score. The algorithm also provides a refined list of most frequent sophisticated patterns typical for both emotive and non-emotive cont...
In computational linguistics, the increasing interest of the detection of emotional and personality ...
This paper describes the National Research Council of Canada\u2019s submission to the 2011 i2b2 NLP ...
In the past years, an important volume of research in Natural Language Processing has concentrated o...
AbstractThis paper presents our research in detection of emotive (emotionally loaded) sentences. The...
ist.hokudai.ac.jp In this research we focus on discriminat-ing between emotive (emotionally loaded) ...
International audienceThe ANR EmotiRob project aims at detecting emotions in an original application...
Abstract. The ANR EmotiRob project aims at detecting emotions in an original application context: re...
In the context of text understanding, computational methods are used to study how humans utilize sty...
This paper summarizes several lexical methods for more comprehensive affect recognition in text usin...
We propose a highly effective method of analysis of emotiveness in utterances, which clearly outperf...
AbstractA new quantitative approach to identifying emotionally colored texts that reflect the excite...
This survey describes recent works in the field of Emotion Detection from text, being a part of the ...
The literature regarding Persian text mining indicates that most studies are conducted to detect pol...
We propose a method for affect analysis of textual input in Japanese supported with Web mining. The ...
Sentiment analysis is one of the recent, highly dynamic fields in Natural Language Processing. Altho...
In computational linguistics, the increasing interest of the detection of emotional and personality ...
This paper describes the National Research Council of Canada\u2019s submission to the 2011 i2b2 NLP ...
In the past years, an important volume of research in Natural Language Processing has concentrated o...
AbstractThis paper presents our research in detection of emotive (emotionally loaded) sentences. The...
ist.hokudai.ac.jp In this research we focus on discriminat-ing between emotive (emotionally loaded) ...
International audienceThe ANR EmotiRob project aims at detecting emotions in an original application...
Abstract. The ANR EmotiRob project aims at detecting emotions in an original application context: re...
In the context of text understanding, computational methods are used to study how humans utilize sty...
This paper summarizes several lexical methods for more comprehensive affect recognition in text usin...
We propose a highly effective method of analysis of emotiveness in utterances, which clearly outperf...
AbstractA new quantitative approach to identifying emotionally colored texts that reflect the excite...
This survey describes recent works in the field of Emotion Detection from text, being a part of the ...
The literature regarding Persian text mining indicates that most studies are conducted to detect pol...
We propose a method for affect analysis of textual input in Japanese supported with Web mining. The ...
Sentiment analysis is one of the recent, highly dynamic fields in Natural Language Processing. Altho...
In computational linguistics, the increasing interest of the detection of emotional and personality ...
This paper describes the National Research Council of Canada\u2019s submission to the 2011 i2b2 NLP ...
In the past years, an important volume of research in Natural Language Processing has concentrated o...