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A Deep Multi-Level Attentive network for Multimodal Sentiment Analysis [article]

Ashima Yadav, Dinesh Kumar Vishwakarma
2020 arXiv   pre-print
Then we model the correlation between the image regions and semantics of the word by extracting the textual features related to the bi-attentive visual features by applying semantic attention.  ...  Multimodal sentiment analysis has attracted increasing attention with broad application prospects.  ...  This enhances the performance of the multimodal data for sentiment analysis.  ... 
arXiv:2012.08256v1 fatcat:lfx66b6dinfolnfjjngjfl6qey

Multidimensional Extra Evidence Mining for Image Sentiment Analysis

Hongbin Zhang, Jinpeng Wu, Haowei Shi, Ziliang Jiang, Donghong Ji, Tian Yuan, Guangli Li
2020 IEEE Access  
Image sentiment analysis is conducted based on the cross-modal sentimental semantics and a general classifier.  ...  sentimental semantics among diverse image features.  ...  Based on the mined cross-modal sentimental semantics and a general classifier, we train a classification model for image sentiment analysis. B.  ... 
doi:10.1109/access.2020.2999128 fatcat:zy2cxcydhfeolm57wcxyw3egri

GIF Video Sentiment Detection Using Semantic Sequence

Dazhen Lin, Donglin Cao, Yanping Lv, Zheng Cai
2017 Mathematical Problems in Engineering  
However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem.  ...  Our experiment results on GSO-2016 (GIF Sentiment Ontology) data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art  ...  According to the visual content type, recent studies can be divided into two types: image sentiment analysis and video sentiment analysis. For image sentiment analysis, You et al.  ... 
doi:10.1155/2017/6863174 fatcat:7pblr5zti5g4tlo5gxziwibj64

Multimodal Sentimental Analysis for Tweets

T. Nandhini, S. Nivetha, R. Pavithra, Dr.S.T. Veena
2020 International Journal of Recent Trends in Engineering and Research  
The proposed approach explores the correlation between the image and the text, followed by a multimodal sentiment analysis method.  ...  Consequently, the conventional text-based sentiment analysis has evolved into more complicated studies of multimodal sentiment analysis.  ...  By doing this, we can enhance sentiment prediction accuracy compared with only using text or image feature.  ... 
doi:10.23883/ijrter.conf.20200315.031.nlm7o fatcat:y63ai7p2yfehpon2aeb7ypo4aa

Visual Sentiment Analysis on Social Media Data

Harshala Bhoir, K. Jayamalini
2021 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
Visual sentiment analysis is the way to automatically recognize positive and negative emotions from images, videos, graphics, stickers etc.  ...  The proposed System will extract three views visual view, subjective text view and objective text view of social media image and will give sentiment polarity positive, negative or neutral based on hypothesis  ...  ., text, image, video, and audio) to perform Image Classification, Visual Sentiment Analysis [10] , Image Retrieval, and Event Classification by exploiting social media contents.  ... 
doi:10.32628/cseit2174101 fatcat:6kenjwhwtnez7gbjhidjmkehly

Sentiment Analysis of Chinese Paintings Based on Lightweight Convolutional Neural Network

Jianying Bian, Xiaoying Shen, Shan Zhong
2021 Wireless Communications and Mobile Computing  
To verify the effectiveness of the optimized SqueezeNet model used in the sentiment analysis of Chinese paintings, four kinds of sentiment classifications were carried out on the multitheme Chinese paintings  ...  On the one hand, expand the model width to obtain more effective Chinese painting sentiment features for classification tasks, thereby improving the classification accuracy of the model.  ...  Moreover, different objects in the same image may represent different sentiment classifications, such as the semantic segmentation problem in image sentiment analysis, which needs to be further studied  ... 
doi:10.1155/2021/6097295 fatcat:ojkhpqlk7na55heh6ch6tvbopq

Discovering Sentimental Interaction via Graph Convolutional Network for Visual Sentiment Prediction

Lifang Wu, Heng Zhang, Sinuo Deng, Ge Shi, Xu Liu
2021 Applied Sciences  
With the popularity of online opinion expressing, automatic sentiment analysis of images has gained considerable attention.  ...  Most methods focus on effectively extracting the sentimental features of images, such as enhancing local features through saliency detection or instance segmentation tools.  ...  We propose an end-to-end image sentiment analysis framework that employs GCN to extract sentimental interaction characteristics among objects.  ... 
doi:10.3390/app11041404 fatcat:2i4v2ce6fzg5lgsehdk24ohs3y

OutdoorSent: Sentiment Analysis of Urban Outdoor Images by Using Semantic and Deep Features [article]

Wyverson B. de Oliveira, Leyza B. Dorini, Rodrigo Minetto, Thiago H. Silva
2019 arXiv   pre-print
We compare the performance of state-of-the-art ConvNet architectures, and one specifically designed for sentiment analysis.  ...  For instance, particular areas of the city tend to concentrate more images of a specific class of sentiment, which are also correlated with median income, opening up opportunities in different fields.  ...  This study investigates if semantic attributes (YOLO and SUN) help to enhance the performance of ConvNets for sentiment analysis in outdoor images.  ... 
arXiv:1906.02331v3 fatcat:6ji2wv6mffapjoceeefmou5suu

Multi-Level Context Pyramid Network for Visual Sentiment Analysis

Haochun Ou, Chunmei Qing, Xiangmin Xu, Jianxiu Jin
2021 Sensors  
sentiment analysis by combining local and global representations to improve the classification performance.  ...  Finally, different levels of context features are combined to obtain the multi-cue sentimental feature for image sentiment classification.  ...  [22] used the excellent model of target recognition and scene classification competition to generate objects and scene category labels as high-level semantic features for image sentiment classification  ... 
doi:10.3390/s21062136 pmid:33803744 fatcat:ddwzqg5yinfk3g2nqkf256bhwi

A Survey on Visual Sentiment Analysis

Alessandro Ortis, Giovanni Maria Farinella, Sebastiano Battiato
2020 IET Image Processing  
Visual Sentiment Analysis aims to understand how images affect people, in terms of evoked emotions.  ...  To this aim, this paper considers a structured formalization of the problem which is usually used for the analysis of text, and discusses it's suitability in the context of Visual Sentiment Analysis.  ...  A number of sub-images is extracted and the sentiment analysis is performed on each sub-image obtained by exploiting methods such as multi-object detection, image segmentation, objectness extraction [  ... 
doi:10.1049/iet-ipr.2019.1270 fatcat:cuhaluxac5ar5ky4rkoqmug6x4

Sentiment Interaction Distillation Network for Image Sentiment Analysis

Lifang Wu, Sinuo Deng, Heng Zhang, Ge Shi
2022 Applied Sciences  
Inspired by the observation that interaction among objects can impact the sentiment of images, we propose the Sentiment Interaction Distillation (SID) Network, which utilizes object sentimental interaction  ...  It is demonstrated that the reasonable use of interaction features can improve the performance of sentiment analysis.  ...  [19] achieved a higher performance by enhancing the local features in the image, which proves that local features have a promoting effect on image sentiment classification. Further, Yang et al.  ... 
doi:10.3390/app12073474 fatcat:gakesvsiu5arzlka2janplzvnm

Fusion of Sentiment and Asset Price Predictions for Portfolio Optimization [article]

Mufhumudzi Muthivhi, Terence L. van Zyl
2022 arXiv   pre-print
To this end, the study uses a Semantic Attention Model to predict sentiment towards an asset.  ...  This paper aims to unpack and develop an enhanced understanding of the sentiment aware portfolio selection problem.  ...  The analysis details that price and investor sentiment is indeed correlated.  ... 
arXiv:2203.05673v1 fatcat:gwuhupujxjff5ow7sy2vwocqvu


Vedashree C.R and Sowmyashree S. V. Sunil Kumar
2022 Zenodo  
This paper introduces the area of Image Sentiment Analysis and examines the issues that it raises.  ...  Sentiment analysis of such large-scale visual content can aid in better extracting user sentiments toward events or themes, such as those in image tweets, so that sentiment prediction from visual content  ...  Sentiment Holder:-Almost all works on Image Sentiment Analysis ignore the sentiment holder or only evaluate the image publisher's sentiment implicitly.  ... 
doi:10.5281/zenodo.6507385 fatcat:t4ppdghzlvg2neswfsfovbvoai

Influencing Factors of Learning Experience in Online Large-Class Teaching ——Semantic Analysis Based on Students' Classroom Feedback Language Materials

Qing Liu
2021 Converter  
Pearson correlation analysis on the score of text sentiment and the statistical data of questionnaire survey.The results show that the results of text semantic analysis and questionnaire survey have the  ...  According to the text semantic analysis and questionnaire survey on students' learning feedback in online large classes,the NLPIR-Parser big-data semantic intelligent analysis platform is used in this  ...  field, there are few researches on sentiment classification of joy, anger and sadness [21] [22] , thus learners' sentiment analysis model with the ability of realizing multi-level sentiment classification  ... 
doi:10.17762/converter.162 fatcat:bp44ckksmrcnxdf5lerojvv3we

A Deeper Look at Human Visual Perception of Images

Shaojing Fan, Bryan L. Koenig, Qi Zhao, Mohan S. Kankanhalli
2020 SN Computer Science  
A common approach is to link lower level image features with higher level properties, and train a computational model to perform classification using human-annotated ground truth.  ...  Statistical analyses indicate varying importance of holistic cues, color information, semantics, and saliency on different types of attributes.  ...  affected by image semantics.  ... 
doi:10.1007/s42979-019-0061-5 fatcat:c7if7p6765hnzpdvef35rf5y7m
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