DeepAI AI Chat
Log In Sign Up

Exploring Fine-Tuned Embeddings that Model Intensifiers for Emotion Analysis

04/05/2019
by   Laura Bostan, et al.
University of Stuttgart
0

Adjective phrases like "a little bit surprised", "completely shocked", or "not stunned at all" are not handled properly by currently published state-of-the-art emotion classification and intensity prediction systems which use pre-dominantly non-contextualized word embeddings as input. Based on this finding, we analyze differences between embeddings used by these systems in regard to their capability of handling such cases. Furthermore, we argue that intensifiers in context of emotion words need special treatment, as is established for sentiment polarity classification, but not for more fine-grained emotion prediction. To resolve this issue, we analyze different aspects of a post-processing pipeline which enriches the word representations of such phrases. This includes expansion of semantic spaces at the phrase level and sub-word level followed by retrofitting to emotion lexica. We evaluate the impact of these steps with A La Carte and Bag-of-Substrings extensions based on pretrained GloVe, Word2vec, and fastText embeddings against a crowd-sourced corpus of intensity annotations for tweets containing our focus phrases. We show that the fastText-based models do not gain from handling these specific phrases under inspection. For Word2vec embeddings, we show that our post-processing pipeline improves the results by up to 8 densely populated with intensifiers.

READ FULL TEXT
03/13/2018

Enhanced Word Representations for Bridging Anaphora Resolution

Most current models of word representations(e.g.,GloVe) have successfull...
04/18/2021

Guilt by Association: Emotion Intensities in Lexical Representations

What do word vector representations reveal about the emotions associated...
04/17/2017

FEUP at SemEval-2017 Task 5: Predicting Sentiment Polarity and Intensity with Financial Word Embeddings

This paper presents the approach developed at the Faculty of Engineering...
05/21/2023

JNV Corpus: A Corpus of Japanese Nonverbal Vocalizations with Diverse Phrases and Emotions

We present JNV (Japanese Nonverbal Vocalizations) corpus, a corpus of Ja...
08/13/2017

Semi-supervised emotion lexicon expansion with label propagation and specialized word embeddings

There exist two main approaches to automatically extract affective orien...
05/29/2020

Stance Prediction for Contemporary Issues: Data and Experiments

We investigate whether pre-trained bidirectional transformers with senti...
09/18/2021

Augmenting semantic lexicons using word embeddings and transfer learning

Sentiment-aware intelligent systems are essential to a wide array of app...