Journal ArticleDOI
YouTube Movie Reviews: Sentiment Analysis in an Audio-Visual Context
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TLDR
Experimental results indicate that training on written movie reviews is a promising alternative to exclusively using (spoken) in-domain data for building a system that analyzes spoken movie review videos, and that language-independent audio-visual analysis can compete with linguistic analysis.Abstract:
This work focuses on automatically analyzing a speaker's sentiment in online videos containing movie reviews. In addition to textual information, this approach considers adding audio features as typically used in speech-based emotion recognition as well as video features encoding valuable valence information conveyed by the speaker. Experimental results indicate that training on written movie reviews is a promising alternative to exclusively using (spoken) in-domain data for building a system that analyzes spoken movie review videos, and that language-independent audio-visual analysis can compete with linguistic analysis.read more
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Book ChapterDOI
Review of Learning-Based Techniques of Sentiment Analysis for Security Purposes
Mohammed Boukabous,Mostafa Azizi +1 more
TL;DR: In this paper, the authors provide an overview of the existing literature of learning-based methods regarding the context of sentiment analysis and security intelligence in exchanged messages based on sentiment analysis techniques and their findings can serve as a potential basis for future research directions.
Journal ArticleDOI
A prosody-based vector-space model of dialog activity for information retrieval
TL;DR: A new way to use prosodic information in search is proposed, based on a vector-space model, where each point in time maps to a point in a vector space whose dimensions are derived from numerous prosodic features of the local context.
Proceedings ArticleDOI
A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts
TL;DR: Wang et al. as discussed by the authors proposed a sentiment analysis and key entity detection approach based on BERT, which is applied in online financial text mining and public opinion analysis in social media.
Journal ArticleDOI
Enhanced Video Analytics for Sentiment Analysis Based on Fusing Textual, Auditory and Visual Information
TL;DR: The proposed approach of combining different modalities can lead to more accurate prediction of speaker’s sentiment with above 94% accuracy and the effectiveness of various combinations of modalities is verified using multi-level fusion (feature, score and decision).
Journal ArticleDOI
Multi-Fusion Residual Memory Network for Multimodal Human Sentiment Comprehension
TL;DR: In this paper , a hierarchical learning architecture is introduced to classify utterance-level sentiment, which explicitly models time-restricted interactions by incorporating information across modalities at the same time step.
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Posted Content
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
TL;DR: A simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (Thumbs down) if the average semantic orientation of its phrases is positive.
Proceedings Article
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
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Correlation-based Feature Selection for Machine Learning
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Proceedings ArticleDOI
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
Bo Pang,Lillian Lee +1 more
TL;DR: This paper proposed a machine learning method that applies text-categorization techniques to just the subjective portions of the document, extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints.
Journal ArticleDOI
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
TL;DR: In this paper, the authors discuss human emotion perception from a psychological perspective, examine available approaches to solving the problem of machine understanding of human affective behavior, and discuss important issues like the collection and availability of training and test data.