Text‐based emotion detection: Advances, challenges, and opportunities
FA Acheampong, C Wenyu… - Engineering …, 2020 - Wiley Online Library
Emotion detection (ED) is a branch of sentiment analysis that deals with the extraction and
analysis of emotions. The evolution of Web 2.0 has put text mining and analysis at the …
analysis of emotions. The evolution of Web 2.0 has put text mining and analysis at the …
[HTML][HTML] Beyond rating scales: With targeted evaluation, large language models are poised for psychological assessment
In this narrative review, we survey recent empirical evaluations of AI-based language
assessments and present a case for the technology of large language models to be poised …
assessments and present a case for the technology of large language models to be poised …
Measuring emotions in the covid-19 real world worry dataset
The COVID-19 pandemic is having a dramatic impact on societies and economies around
the world. With various measures of lockdowns and social distancing in place, it becomes …
the world. With various measures of lockdowns and social distancing in place, it becomes …
Deep learning for affective computing: Text-based emotion recognition in decision support
Emotions widely affect human decision-making. This fact is taken into account by affective
computing with the goal of tailoring decision support to the emotional states of individuals …
computing with the goal of tailoring decision support to the emotional states of individuals …
Estimating geographic subjective well-being from Twitter: A comparison of dictionary and data-driven language methods
Researchers and policy makers worldwide are interested in measuring the subjective well-
being of populations. When users post on social media, they leave behind digital traces that …
being of populations. When users post on social media, they leave behind digital traces that …
Automated accurate speech emotion recognition system using twine shuffle pattern and iterative neighborhood component analysis techniques
Speech emotion recognition is one of the challenging research issues in the knowledge-
based system and various methods have been recommended to reach high classification …
based system and various methods have been recommended to reach high classification …
Emobank: Studying the impact of annotation perspective and representation format on dimensional emotion analysis
We describe EmoBank, a corpus of 10k English sentences balancing multiple genres, which
we annotated with dimensional emotion metadata in the Valence-Arousal-Dominance (VAD) …
we annotated with dimensional emotion metadata in the Valence-Arousal-Dominance (VAD) …
The MuSe 2021 multimodal sentiment analysis challenge: sentiment, emotion, physiological-emotion, and stress
Multimodal Sentiment Analysis (MuSe) 2021 is a challenge focusing on the tasks of
sentiment and emotion, as well as physiological-emotion and emotion-based stress …
sentiment and emotion, as well as physiological-emotion and emotion-based stress …
An analysis of annotated corpora for emotion classification in text
LAM Bostan, R Klinger - 2018 - fis.uni-bamberg.de
Several datasets have been annotated and published for classification of emotions. They
differ in several ways:(1) the use of different annotation schemata (eg, discrete label sets …
differ in several ways:(1) the use of different annotation schemata (eg, discrete label sets …
Tree-structured regional CNN-LSTM model for dimensional sentiment analysis
Dimensional sentiment analysis aims to recognize continuous numerical values in multiple
dimensions such as the valence-arousal (VA) space. Compared to the categorical approach …
dimensions such as the valence-arousal (VA) space. Compared to the categorical approach …