Ester Boldrini


2017

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Towards the Improvement of Automatic Emotion Pre-annotation with Polarity and Subjective Information
Lea Canales | Walter Daelemans | Ester Boldrini | Patricio Martínez-Barco
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017

Emotion detection has a high potential positive impact on the benefit of business, society, politics or education. Given this, the main objective of our research is to contribute to the resolution of one of the most important challenges in textual emotion detection: emotional corpora annotation. This will be tackled by proposing a semi-automatic methodology. It consists in two main phases: (1) an automatic process to pre-annotate the unlabelled sentences with a reduced number of emotional categories; and (2) a manual process of refinement where human annotators will determine which is the dominant emotion between the pre-defined set. Our objective in this paper is to show the pre-annotation process, as well as to evaluate the usability of subjective and polarity information in this process. The evaluation performed confirms clearly the benefits of employing the polarity and subjective information on emotion detection and thus endorses the relevance of our approach.

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Ultra-Concise Multi-genre Summarisation of Web2.0: towards Intelligent Content Generation
Elena Lloret | Ester Boldrini | Patricio Martínez-Barco | Manuel Palomar
Proceedings of the MultiLing 2017 Workshop on Summarization and Summary Evaluation Across Source Types and Genres

The electronic Word of Mouth has become the most powerful communication channel thanks to the wide usage of the Social Media. Our research proposes an approach towards the production of automatic ultra-concise summaries from multiple Web 2.0 sources. We exploit user-generated content from reviews and microblogs in different domains, and compile and analyse four types of ultra-concise summaries: a)positive information, b) negative information; c) both or d) objective information. The appropriateness and usefulness of our model is demonstrated by its successful results and great potential in real-life applications, thus meaning a relevant advancement of the state-of-the-art approaches.

2016

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Innovative Semi-Automatic Methodology to Annotate Emotional Corpora
Lea Canales | Carlo Strapparava | Ester Boldrini | Patricio Martínez-Barco
Proceedings of the Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media (PEOPLES)

Detecting depression or personality traits, tutoring and student behaviour systems, or identifying cases of cyber-bulling are a few of the wide range of the applications, in which the automatic detection of emotion is a crucial element. Emotion detection has the potential of high impact by contributing the benefit of business, society, politics or education. Given this context, the main objective of our research is to contribute to the resolution of one of the most important challenges in textual emotion detection task: the problems of emotional corpora annotation. This will be tackled by proposing of a new semi-automatic methodology. Our innovative methodology consists in two main phases: (1) an automatic process to pre-annotate the unlabelled sentences with a reduced number of emotional categories; and (2) a refinement manual process where human annotators will determine which is the predominant emotion between the emotional categories selected in the phase 1. Our proposal in this paper is to show and evaluate the pre-annotation process to analyse the feasibility and the benefits by the methodology proposed. The results obtained are promising and allow obtaining a substantial improvement of annotation time and cost and confirm the usefulness of our pre-annotation process to improve the annotation task.

2012

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Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis
Alexandra Balahur | Andres Montoyo | Patricio Martinez Barco | Ester Boldrini
Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis

2011

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Evaluating the Robustness of EmotiBlog for Sentiment Analysis and Opinion Mining
Ester Boldrini | Javi Fernández | José Manuel Gómez | Patricio Martínez-Barco
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011

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Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA 2.011)
Alexandra Balahur | Ester Boldrini | Andres Montoyo | Patricio Martinez-Barco
Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA 2.011)

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EMOCause: An Easy-adaptable Approach to Extract Emotion Cause Contexts
Irene Russo | Tommaso Caselli | Francesco Rubino | Ester Boldrini | Patricio Martínez-Barco
Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA 2.011)

2010

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EmotiBlog: A Finer-Grained and More Precise Learning of Subjectivity Expression Models
Ester Boldrini | Alexandra Balahur | Patricio Martínez-Barco | Andrés Montoyo
Proceedings of the Fourth Linguistic Annotation Workshop

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Going Beyond Traditional QA Systems: Challenges and Keys in Opinion Question Answering
Alexandra Balahur | Ester Boldrini | Andrés Montoyo | Patricio Martínez-Barco
Coling 2010: Posters

2009

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A Comparative Study of Open Domain and Opinion Question Answering Systems for Factual and Opinionated Queries
Alexandra Balahur | Ester Boldrini | Andrés Montoyo | Patricio Martínez-Barco
Proceedings of the International Conference RANLP-2009

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Summarizing Threads in Blogs Using Opinion Polarity
Alexandra Balahur | Elena Lloret | Ester Boldrini | Andrés Montoyo | Manuel Palomar | Patricio Martínez-Barco
Proceedings of the Workshop on Events in Emerging Text Types

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Opinion and Generic Question Answering Systems: a Performance Analysis
Alexandra Balahur | Ester Boldrini | Andrés Montoyo | Patricio Martínez-Barco
Proceedings of the ACL-IJCNLP 2009 Conference Short Papers