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Visual Sentiment Analysis with Active Learning

Jie Chen, Qirong Mao, Luoyang Xue
2020 IEEE Access  
In this paper, we propose a novel active learning framework, which uses few labeled training samples to achieve an effective sentiment analysis model.  ...  Visual Sentiment Analysis (VSA) has attracted wide attention since more and more people are willing to express their emotion and opinions via visual contents on social media.  ...  VISUAL SENTIMENT ANALYSIS WITH ACTIVE LEARNING In this section, we present our new method using active learning in VSA.  ... 
doi:10.1109/access.2020.3024948 fatcat:jkiajwkb5nfubfxwvazvuxlayq

Human Sentiment and Activity Recognition in Disaster Situations Using Social Media Images Based on Deep Learning

Amin Muhammad Sadiq, Huynsik Ahn, Young Bok Choi
2020 Sensors  
This paper emphasizes human sentiment in a socially crucial field, namely social media disaster/catastrophe analysis, with associated physical activity analysis.  ...  up new possibilities and opportunities in sentiment and activity analysis.  ...  to completely leverage the ability of visual sentiment and associated human activity analysis.  ... 
doi:10.3390/s20247115 pmid:33322465 pmcid:PMC7763261 fatcat:367dozllmzh5zchqvp3h4nadym

Unsupervised Feature Learning Assisted Visual Sentiment Analysis

Zuhe Li, Yangyu Fan, Fengqin Wang, Weihua Liu
2016 International Journal of Multimedia and Ubiquitous Engineering  
Visual sentiment analysis which aims to understand the emotion and sentiment in visual content has attracted more and more attention.  ...  In this paper, we propose a hybrid approach for visual sentiment concept classification with an unsupervised feature learning architecture called convolutional autoencoder.  ...  Inspired by the recent success of deep learning in visual sentiment analysis, we are interested in the feasibility of classifying visual sentiment concepts with unsupervised learning algorithms, which  ... 
doi:10.14257/ijmue.2016.11.10.11 fatcat:nzqmybcptjf7fbfetjyeftbpyu

Sentiment and Emotion Analysis for Social Multimedia

Quanzeng You
2016 Proceedings of the 2016 ACM on Multimedia Conference - MM '16  
The image tweet is a great example of multimodal sentiment. In this research, we focus on sentiment analysis based on visual and multimedia information analysis.  ...  However, existing sentiment analysis typically focuses on textual information regardless of the visual content, which may be as informative in expressing people's sentiments and opinions.  ...  These results have suggested that online users' opinions or sentiments are closely correlated with our real-world activities.  ... 
doi:10.1145/2964284.2971475 dblp:conf/mm/You16 fatcat:iabsyivuezgwbbi6x3ygvvispu

Smart Citizen Sensing: A Proposed Computational System with Visual Sentiment Analysis and Big Data Architecture

Kaoutar Ben, Mohammed Bouhorma, Mohamed Ben
2016 International Journal of Computer Applications  
This paper presents a novel approach to perform visual sentiment analysis of big visual data shared on social networks (such as Facebook, Twitter, LinkedIn, and Pinterest) using transfer learning.  ...  Thus, they become sensing nodes-or citizen sensors-within smart-cities with both static information and a constantly emitting activity system.  ...  PROPOSED COMPUTATIONAL SYSTEM: VISUAL SENTIMENT PREDICTION USING TRANSFER LEARNING While Researchers have largely relied on textual sentiment analysis, research on visual sentiment analysis is far behind  ... 
doi:10.5120/ijca2016911880 fatcat:sqvunitc2bd5zinhk2aaklqxvq

Polarity and Intensity: the Two Aspects of Sentiment Analysis [article]

Leimin Tian, Catherine Lai, Johanna D. Moore
2018 arXiv   pre-print
Current multimodal sentiment analysis frames sentiment score prediction as a general Machine Learning task. However, what the sentiment score actually represents has often been overlooked.  ...  Our experiments show that sentiment analysis benefits from multi-task learning, and individual modalities differ when conveying the polarity and intensity aspects of sentiment.  ...  Multimodal Sentiment Analysis with Multi-Task Learning In this study, we apply multi-task learning to sentiment analysis using the CMU-MOSI database.  ... 
arXiv:1807.01466v1 fatcat:nohq4rex3zb2dgtqoigzqnt364

HMTL: Heterogeneous Modality Transfer Learning for Audio-visual Sentiment Analysis

Sanghyun Seo, Sanghyuck Na, Juntae Kim
2020 IEEE Access  
In this paper, we propose heterogeneous modality transfer learning (HMTL) to utilize the knowledge of aligned text data as a source modality in transfer learning to improve audio-visual sentiment analysis  ...  INDEX TERMS Multimodal sentiment analysis, heterogeneous transfer learning, data fusion.  ...  In particular, due to the recent advances in deep learning techniques, various sentiment analysis studies using large amounts of text data actively have been proposed.  ... 
doi:10.1109/access.2020.3006563 fatcat:qs2ld6ly3nhppmejwlbhy36guu

Sentiment Analysis from Images of Natural Disasters [article]

Syed Zohaib, Kashif Ahmad, Nicola Conci, Ala Al-Fuqaha
2019 arXiv   pre-print
We analyze how visual sentiment analysis can improve the results for the end-users/beneficiaries in terms of mining information from social media.  ...  We also identify the challenges and related applications, which could help defining a benchmark for future research efforts in visual sentiment analysis.  ...  CNN) and a transfer learning method, where the model pretrained on ImageNet is fine-tuned for visual sentiment analysis.  ... 
arXiv:1910.04416v1 fatcat:2wqq6kkfkfduhiegdxsiivofja

Convolutional Neural Networks for Multimedia Sentiment Analysis [chapter]

Guoyong Cai, Binbin Xia
2015 Lecture Notes in Computer Science  
Two individual CNN architectures are used for learning textual features and visual features, which can be combined as input of another CNN architecture for exploiting the internal relation between text  ...  Compared to sentiment analysis of texts and images separately, the combination of text and image may reveal tweet sentiment more adequately.  ...  In addition, several researches employed deep learning methods [6, 7] for visual sentiment analysis. Xu et al. [6] proposed a novel visual sentiment prediction framework with CNN.  ... 
doi:10.1007/978-3-319-25207-0_14 fatcat:qtim3nkrmnegpjzsxl273ligie

Visual Learning of Semantic Concepts in Social Multimedia

Damian Borth
2014 Künstliche Intelligenz  
/testing benchmark for visual sentiment analysis.  ...  His research interests includes visual learning, multimedia retrieval and social media analysis. 1 http://visual-sentiment-ontology.appspot.com.  ... 
doi:10.1007/s13218-014-0328-x fatcat:hq267u3qnreffcmypn63qn2zmy

Active learning for sentiment analysis on data streams: Methodology and workflow implementation in the ClowdFlows platform

Janez Kranjc, Jasmina Smailović, Vid Podpečan, Miha Grčar, Martin Žnidaršič, Nada Lavrač
2015 Information Processing & Management  
The advanced features of ClowdFlows are demonstrated on a sentiment analysis use case, using active learning with a linear Support Vector Machine for learning sentiment classification models to be applied  ...  This paper describes ClowdFlows, a cloud-based scientific workflow platform, and its extensions enabling the analysis of data streams and active learning.  ...  The proposed sentiment analysis and active learning methods are presented in Section 4.  ... 
doi:10.1016/j.ipm.2014.04.001 fatcat:rm6hgc5nofhpren3imcxh3p7wm

An Integrated Deep Learning and Belief Rule-Based Expert System for Visual Sentiment Analysis under Uncertainty

Sharif Noor Zisad, Etu Chowdhury, Mohammad Shahadat Hossain, Raihan Ul Islam, Karl Andersson
2021 Algorithms  
Our integrated expert system outperforms the state-of-the-art methods of visual sentiment analysis with promising results. The integrated system can classify images with 86% accuracy.  ...  On account of this, we develop a visual sentiment analysis system, which can classify image expression.  ...  (3) Why and how we combine Deep Learning with BRBES? We compose the remainder of this paper as follows: Section 2 surveys related work on visual sentiment analysis.  ... 
doi:10.3390/a14070213 fatcat:jb63onrfbvaqdlsyboo52my3si

Visual Sentiment Analysis with Network in Network

Zuhe Li, Yangyu Fan, Fengqin Wang
2016 International Journal of Signal Processing, Image Processing and Pattern Recognition  
As a complement to textual sentiment analysis, visual sentiment analysis intends to provide more robust information for data analytics by extracting emotion and sentiment toward topics and events from  ...  Inspired by recent works that applied deep convolutional neural networks (CNN) to this challenging problem, we proposed a framework for image sentiment analysis with a novel deep neural network called  ...  These successes therefore indicated the feasibility of applying deep learning algorithms to visual sentiment analysis.  ... 
doi:10.14257/ijsip.2016.9.9.19 fatcat:dvyx3f5bqzgztjoa6sknl43fem

Analysis on Different Techniques Used For Sentimental Analysis

Praveen Kulkarni,, Dr. Rajesh T.M
2019 International Journal of Research in Advent Technology  
A good deal of analysis has been done to research the feeling of human matter knowledge. There's an awfully restricted work that focuses on the sentimental analysis of image knowledge.  ...  The challenge lies within the linguistics gap between low-level visual characteristics and feelings of a better level image.Our review makes use of the link between the visual and therefore the relevant  ...  Visual Sentiment Analysis for Social pictures exploitation Transfer Learning Approach [14] during this paper, they counsel a clever visual sentiment analysis framework exploitation transfer learning  ... 
doi:10.32622/ijrat.72201947 fatcat:yq4rawimqzh5dkuq7wfnfpq2oq

Visual and Textual Sentiment Analysis Using Deep Fusion Convolutional Neural Networks [article]

Xingyue Chen, Yunhong Wang, Qingjie Liu
2017 arXiv   pre-print
learn textual and visual sentiment representations from training examples.  ...  Sentiment analysis is attracting more and more attentions and has become a very hot research topic due to its potential applications in personalized recommendation, opinion mining, etc.  ...  [14] proposed a cross-modality consistent regression (CCR) scheme for joint textual-visual sentiment analysis. Their approach employed deep visual and textual features to learn a regression model.  ... 
arXiv:1711.07798v1 fatcat:wwg7euw24fcldbzozdseokerc4
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