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Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context.
Emotion recognition in conversation (ERC) is a sub-field of emotion recognition, that focuses on mining human emotions from conversations or dialogues having two or more interlocutors. [1] The datasets in this field are usually derived from social platforms that allow free and plenty of samples, often containing multimodal data (i.e., some ...
In 2006, a first W3C Incubator Group, [3] the Emotion Incubator Group (EmoXG), was set up "to investigate a language to represent the emotional states of users and the emotional states simulated by user interfaces" [4] with the final Report published on 10 July 2007.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Vietnamese Social Media Emotion Corpus (UIT-VSMEC) Users’ Facebook Comments. Comments 6,927 Text Classification 1997 [21] Nguyen et al. Vietnamese Open-domain Complaint Detection dataset (ViOCD) Customer product reviews Comments 5,485 Text Classification 2021 [22] Nguyen et al. ViHOS: Hate Speech Spans Detection for Vietnamese Social Media Texts
A facial expression database is a collection of images or video clips with facial expressions of a range of emotions.Well-annotated (emotion-tagged) media content of facial behavior is essential for training, testing, and validation of algorithms for the development of expression recognition systems.
The main difference between basic emotion models and appraisal models is that appraisal models assume that there is a cognitive antecedent that determines which emotion is triggered. Emotions go beyond simple judgments of stimuli in our environment and are forms of motivation that drive action. [24]