Emotions and NLP: Future Directions

@inproceedings{Strapparava2016EmotionsAN,
  title={Emotions and NLP: Future Directions},
  author={Carlo Strapparava},
  booktitle={WASSA@NAACL-HLT},
  year={2016}
}
Emotions are not linguistic entities but they are conveniently expressed through the language. Feelings influence actions, thoughts and of course our way of communicate. It was more than twelve years ago that we developed WordNet-Affect (Strapparava and Valitutti, 2004), and I remember that at that time several people questioned about the utility and even the possibility of studying emotions using computational linguistics techniques. In the recent years, nonetheless there has been a… 
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10 Citations
Background Citations
8
Methods Citations
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10 Citations

Modeling Word Emotion in Historical Language: Quantity Beats Supposed Stability in Seed Word Selection

The first gold standard for historical word emotions is presented, which was created by scholars with proficiency in the respective language stages and covers both English and German, and indicates that hand-selecting small sets of seed words with supposedly stable emotional meaning is actually harm- rather than helpful.

Inducing Affective Lexical Semantics in Historical Language

It is found that limiting the training set to words of supposedly stable emotional meaning does in fact decrease performance, rather than boosting it, and this contribution thus elaborates algorithmic and experimental results which form the basis of some of the later publications.

Exploring Emotion Embedding and the Dimensional Model of Emotion ’ s Predictive Power in Sentiment by

Claims of validity of using the three-dimension emotion model as opposed to the naive polarity model in predicting the sentiment of given text data are explored.

Feelings from the Past—Adapting Affective Lexicons for Historical Emotion Analysis

A novel methodology for measuring affective language in historical text is described by expanding an affective lexicon and jointly adapting it to prior language stages by constructing a lexicon for word-emotion association of 18th and 19th century German.

EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis

EmoBank, a corpus of 10k English sentences balancing multiple genres, is described, which is annotated with dimensional emotion metadata in the Valence-Arousal-Dominance (VAD) representation format and achieves close-to-human performance when mapping between dimensional and categorical formats.

Spanish Emotion Recognition Method Based on Cross-Cultural Perspective

The improved BiLSTM framework is proposed and the attention mechanism is inserted, which enables the shared feature encoder to obtain weighted representation results in the extraction of emotion features, which enhances the generalization ability of the model for text emotion feature recognition.

Multilingual opinion mining

Cada dia se genera gran cantidad de texto en diferentes medios online. Gran parte de ese texto contiene opiniones acerca de multitud de entidades, productos, servicios, etc. Dada la creciente…

Sequential Attention Module for Natural Language Processing

This paper proposes a simple yet effective plug-and-play module, Sequential Attention Module (SAM), on the token embeddings learned from a pre-trained language model, and demonstrates that SAM consistently outperforms the state-of-the-art baselines.

On Unsupervised Methods for Fake News Detection

Tackling the Challenge of Emotion Annotation in Text

References

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Affect Detection in Texts