Sentiment analysis using deep learning approaches: an overview
Nowadays, with the increasing number of Web 2.0 tools, users generate huge amounts of
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …
A survey of textual emotion recognition and its challenges
Textual language is the most natural carrier of human emotion. In natural language
processing, textual emotion recognition (TER) has become an important topic due to its …
processing, textual emotion recognition (TER) has become an important topic due to its …
[HTML][HTML] An effective BERT-based pipeline for Twitter sentiment analysis: A case study in Italian
Over the last decade industrial and academic communities have increased their focus on
sentiment analysis techniques, especially applied to tweets. State-of-the-art results have …
sentiment analysis techniques, especially applied to tweets. State-of-the-art results have …
A survey of state-of-the-art approaches for emotion recognition in text
N Alswaidan, MEB Menai - Knowledge and Information Systems, 2020 - Springer
Emotion recognition in text is an important natural language processing (NLP) task whose
solution can benefit several applications in different fields, including data mining, e-learning …
solution can benefit several applications in different fields, including data mining, e-learning …
Multi-label emotion classification in texts using transfer learning
Social media is a widespread platform that provides a massive amount of user-generated
content that can be mined to reveal the emotions of social media users. This has many …
content that can be mined to reveal the emotions of social media users. This has many …
A survey of multi-label classification based on supervised and semi-supervised learning
M Han, H Wu, Z Chen, M Li, X Zhang - International Journal of Machine …, 2023 - Springer
Multi-label classification algorithms based on supervised learning use all the labeled data to
train classifiers. However, in real life, many of the data are unlabeled, and it is costly to label …
train classifiers. However, in real life, many of the data are unlabeled, and it is costly to label …
MEISD: A multimodal multi-label emotion, intensity and sentiment dialogue dataset for emotion recognition and sentiment analysis in conversations
Emotion and sentiment classification in dialogues is a challenging task that has gained
popularity in recent times. Humans tend to have multiple emotions with varying intensities …
popularity in recent times. Humans tend to have multiple emotions with varying intensities …
TWilBert: Pre-trained deep bidirectional transformers for Spanish Twitter
In recent years, the Natural Language Processing community have been moving from
uncontextualized word embeddings towards contextualized word embeddings. Among …
uncontextualized word embeddings towards contextualized word embeddings. Among …
Transformer-based label set generation for multi-modal multi-label emotion detection
Multi-modal utterance-level emotion detection has been a hot research topic in both multi-
modal analysis and natural language processing communities. Different from traditional …
modal analysis and natural language processing communities. Different from traditional …
Improving multi-label emotion classification via sentiment classification with dual attention transfer network
In this paper, we target at improving the performance of multi-label emotion classification
with the help of sentiment classification. Specifically, we propose a new transfer learning …
with the help of sentiment classification. Specifically, we propose a new transfer learning …