The Experts below are selected from a list of 204 Experts worldwide ranked by ideXlab platform
Pascal Poncelet - One of the best experts on this subject based on the ideXlab platform.
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FEEL: a French Expanded Emotion Lexicon
2019Co-Authors: Amine Abdaoui, Jérôme Azé, Sandra Bringay, Pascal PonceletAbstract:Sentiment analysis allows the semantic evaluation of a piece of text according to the expressed sentiments and opinions. While considerable attention has been given to the polarity (positive, negative) of English words, only few studies were interested in the conveyed emotions (joy, anger, surprise, sadness, etc.) especially in other languages. This report proposes a French Expanded Emotion Lexicon. The elaboration method is based on the semi-automatic translation and expansion to synonyms of the English NRC Word Emotion Association Lexicon (NRC- EmoLex). First, online Translators have been automatically queried in order to create a first version of our new French Expanded Emotion Lexicon (FEEL). Then, a human Professional Translator manually validated the automatically obtained entries and the associated emotions. She agreed with more than 94% of the pre- validated entries (those found by a majority of Translators) and less than 18% of the remaining entries (those found by very few Translators). This result highlights that online tools can be used to get high quality resources with low cost. Annotating a subset of terms by three different annotators shows that the associated sentiments and emotions are consistent.
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FEEL: a French Expanded Emotion Lexicon
Language Resources and Evaluation, 2017Co-Authors: Amine Abdaoui, Jérôme Azé, Sandra Bringay, Pascal PonceletAbstract:Sentiment analysis allows the semantic evaluation of pieces of text according to the expressed sentiments and opinions. While considerable attention has been given to the polarity (positive, negative) of English words, only few studies were interested in the conveyed emotions (joy, anger, surprise, sadness, etc.) especially in other languages. In this paper, we present the elaboration and the evaluation of a new French lexicon considering both polarity and emotion. The elaboration method is based on the semi-automatic translation and expansion to synonyms of the English NRC Word Emotion Association Lexicon (NRC-EmoLex). First, online Translators have been automatically queried in order to create a first version of our new French Expanded Emotion Lexicon (FEEL). Then, a human Professional Translator manually validated the automatically obtained entries and the associated emotions. She agreed with more than 94 % of the pre-validated entries (those found by a majority of Translators) and less than 18 % of the remaining entries (those found by very few Translators). This result highlights that online tools can be used to get high quality resources with low cost. Annotating a subset of terms by three different annotators shows that the associated sentiments and emotions are consistent. Finally, extensive experiments have been conducted to compare the final version of FEEL with other existing French lexicons. Various French benchmarks for polarity and emotion classifications have been used in these evaluations. Experiments have shown that FEEL obtains competitive results for polarity, and significantly better results for basic emotions.
Masayuki Ohishi - One of the best experts on this subject based on the ideXlab platform.
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Validity and reliability of the Japanese version of the kleptomania symptom assessment scale: A comparison between individuals with kleptomania and prisoners in Japan
Comprehensive Psychiatry, 2020Co-Authors: Yuka Asami, Kazutaka Nomura, Hironori Shimada, Hiroyo Ohishi, Masayuki OhishiAbstract:Abstract Introduction In Japan, the rate of recidivism among thieves is high, some of which may be caused by kleptomania. The purpose of this study was to translate the Kleptomania Symptom Assessment Scale (K-SAS) into Japanese and validate its psychometric properties in a Japanese sample. A second purpose of the study was to evaluate the validity of K-SAS to discriminate between individuals with kleptomania and shoplifters not affected by the disorder. Methods The original K-SAS was translated by researchers. The back-translation of the scale into English was conducted by a Professional Translator who was fluent in both languages. The items on the Japanese version of K-SAS were deemed appropriate for the Japanese context after being reviewed by a forensic psychiatry specialist. The sample included 22 kleptomania patients, 26 shoplifters, and 47 healthy adults. We tested the scale properties and validity to discriminate between the three groups. Results The Japanese version of the K-SAS showed adequate reliability and validity. Individuals affected by kleptomania had significantly higher scores than shoplifters and healthy adults. Furthermore, the K-SAS score of kleptomania was not correlated with typical antisocial tendencies. Moreover, the K-SAS score for kleptomania was not correlated with psychometric scales related to obsessive-compulsive disorder and borderline personality disorder. Conclusions The Japanese version of the K-SAS is a useful assessment tool for distinguishing between individuals with kleptomania and shoplifters not affected by the disorder in Japan.
Amine Abdaoui - One of the best experts on this subject based on the ideXlab platform.
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FEEL: a French Expanded Emotion Lexicon
2019Co-Authors: Amine Abdaoui, Jérôme Azé, Sandra Bringay, Pascal PonceletAbstract:Sentiment analysis allows the semantic evaluation of a piece of text according to the expressed sentiments and opinions. While considerable attention has been given to the polarity (positive, negative) of English words, only few studies were interested in the conveyed emotions (joy, anger, surprise, sadness, etc.) especially in other languages. This report proposes a French Expanded Emotion Lexicon. The elaboration method is based on the semi-automatic translation and expansion to synonyms of the English NRC Word Emotion Association Lexicon (NRC- EmoLex). First, online Translators have been automatically queried in order to create a first version of our new French Expanded Emotion Lexicon (FEEL). Then, a human Professional Translator manually validated the automatically obtained entries and the associated emotions. She agreed with more than 94% of the pre- validated entries (those found by a majority of Translators) and less than 18% of the remaining entries (those found by very few Translators). This result highlights that online tools can be used to get high quality resources with low cost. Annotating a subset of terms by three different annotators shows that the associated sentiments and emotions are consistent.
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FEEL: a French Expanded Emotion Lexicon
Language Resources and Evaluation, 2017Co-Authors: Amine Abdaoui, Jérôme Azé, Sandra Bringay, Pascal PonceletAbstract:Sentiment analysis allows the semantic evaluation of pieces of text according to the expressed sentiments and opinions. While considerable attention has been given to the polarity (positive, negative) of English words, only few studies were interested in the conveyed emotions (joy, anger, surprise, sadness, etc.) especially in other languages. In this paper, we present the elaboration and the evaluation of a new French lexicon considering both polarity and emotion. The elaboration method is based on the semi-automatic translation and expansion to synonyms of the English NRC Word Emotion Association Lexicon (NRC-EmoLex). First, online Translators have been automatically queried in order to create a first version of our new French Expanded Emotion Lexicon (FEEL). Then, a human Professional Translator manually validated the automatically obtained entries and the associated emotions. She agreed with more than 94 % of the pre-validated entries (those found by a majority of Translators) and less than 18 % of the remaining entries (those found by very few Translators). This result highlights that online tools can be used to get high quality resources with low cost. Annotating a subset of terms by three different annotators shows that the associated sentiments and emotions are consistent. Finally, extensive experiments have been conducted to compare the final version of FEEL with other existing French lexicons. Various French benchmarks for polarity and emotion classifications have been used in these evaluations. Experiments have shown that FEEL obtains competitive results for polarity, and significantly better results for basic emotions.
Fabienne Morvan - One of the best experts on this subject based on the ideXlab platform.
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Working Alliance Inventory Short Version (WAI SR) translation in Polish with a forward backward translation and a Delphi process
2017Co-Authors: Fabienne MorvanAbstract:Introduction : Therapeutic Alliance (TA) enables an improvement in adherence to treatment and in quality of care. A research group from the Faculty of Medecine in Brest have worked to find a tool to evaluate the TA. This tool can be used not only in practical day to day medicine but also in the training of medical students and in research. A systematic revue of the literature and a RAND/UCLA Appropriateness Method have determined the Working Alliance Inventory Short Version (WAI SR) as the most appropriate scale for evaluating the TA. The objective of the study was to translate into Polish the WAI SR following a validated and referenced method . Method : A forward and backward translation with a Delphi consensus procedure was used as it was the most appropriate method for this study. A research team of 4 experts was asked to translate the WAI SR into Polish. This group consisted of 2 general practicioners, 1 linguist and 1 psychologist. They took into account the cultural context. Experts of the Delphi Round were Polish general practicioners who were fluent in English. After consensus, 2 Poles who were fluent in English made a return backward translation to check the validity of the initial translation. Results : The appropiate forward translation was completed. 24 experts participated in the Delphi Round . Consensus was reached with one Delphi round. The backward translation in English was done by a Professional Translator and an English person who has lived in Poland for 30 years. Conclusion : A Polish translation of the WAI SR is now available, done with a validated method. It can be used in daily medical practise, as a teaching instrument in the training of medical students as well as in medical research.
Jérôme Azé - One of the best experts on this subject based on the ideXlab platform.
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FEEL: a French Expanded Emotion Lexicon
2019Co-Authors: Amine Abdaoui, Jérôme Azé, Sandra Bringay, Pascal PonceletAbstract:Sentiment analysis allows the semantic evaluation of a piece of text according to the expressed sentiments and opinions. While considerable attention has been given to the polarity (positive, negative) of English words, only few studies were interested in the conveyed emotions (joy, anger, surprise, sadness, etc.) especially in other languages. This report proposes a French Expanded Emotion Lexicon. The elaboration method is based on the semi-automatic translation and expansion to synonyms of the English NRC Word Emotion Association Lexicon (NRC- EmoLex). First, online Translators have been automatically queried in order to create a first version of our new French Expanded Emotion Lexicon (FEEL). Then, a human Professional Translator manually validated the automatically obtained entries and the associated emotions. She agreed with more than 94% of the pre- validated entries (those found by a majority of Translators) and less than 18% of the remaining entries (those found by very few Translators). This result highlights that online tools can be used to get high quality resources with low cost. Annotating a subset of terms by three different annotators shows that the associated sentiments and emotions are consistent.
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FEEL: a French Expanded Emotion Lexicon
Language Resources and Evaluation, 2017Co-Authors: Amine Abdaoui, Jérôme Azé, Sandra Bringay, Pascal PonceletAbstract:Sentiment analysis allows the semantic evaluation of pieces of text according to the expressed sentiments and opinions. While considerable attention has been given to the polarity (positive, negative) of English words, only few studies were interested in the conveyed emotions (joy, anger, surprise, sadness, etc.) especially in other languages. In this paper, we present the elaboration and the evaluation of a new French lexicon considering both polarity and emotion. The elaboration method is based on the semi-automatic translation and expansion to synonyms of the English NRC Word Emotion Association Lexicon (NRC-EmoLex). First, online Translators have been automatically queried in order to create a first version of our new French Expanded Emotion Lexicon (FEEL). Then, a human Professional Translator manually validated the automatically obtained entries and the associated emotions. She agreed with more than 94 % of the pre-validated entries (those found by a majority of Translators) and less than 18 % of the remaining entries (those found by very few Translators). This result highlights that online tools can be used to get high quality resources with low cost. Annotating a subset of terms by three different annotators shows that the associated sentiments and emotions are consistent. Finally, extensive experiments have been conducted to compare the final version of FEEL with other existing French lexicons. Various French benchmarks for polarity and emotion classifications have been used in these evaluations. Experiments have shown that FEEL obtains competitive results for polarity, and significantly better results for basic emotions.
