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SAKG-BERT: Enabling Language Representation With Knowledge Graphs for Chinese Sentiment Analysis
2021
IEEE Access
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We propose a sentiment analysis knowledge graph (SAKG)-BERT model that combines sentiment analysis knowledge and the language representation model BERT. ...
Our investigation reveals promising results in sentence completion and sentiment analysis tasks. INDEX TERMS Sentiment analysis, pretraining model, knowledge graph, deep learning, car reviews. ...
Jimmy Huang for his advice and encouragement during the preparation of this article. ...
doi:10.1109/access.2021.3098180
fatcat:hof5rwm7w5eopkehpawvnxcflu
Integrating Semantic and Structural Information with Graph Convolutional Network for Controversy Detection
[article]
2020
arXiv
pre-print
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To overcome the first two limitations, we propose Topic-Post-Comment Graph Convolutional Network (TPC-GCN), which integrates the information from the graph structure and content of topics, posts, and comments ...
Identifying controversial posts on social media is a fundamental task for mining public sentiment, assessing the influence of events, and alleviating the polarized views. ...
This work is supported by the National Nature Science Foundation of China (U1703261). ...
arXiv:2005.07886v1
fatcat:m7hpjisvl5f7nfy6xruihtrpgi
Rumors Detection Based on Lifelong Machine Learning
2022
IEEE Access
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We firstly extracted three types of features based on content, user, and propagation from Weibo events, and proposed three new propagation features and Bidirectional Encoder Representations from Transformers ...
Efficient Lifelong Learning Algorithm (ELLA) on rumors. ...
In recent years, with the success of the Graph Neural Network (GNN), rumor detection algorithms based on GNN had become popular. Bian et al. ...
doi:10.1109/access.2022.3152842
fatcat:ixfplkp5ifdo7nvs76zgdjp5aq
Rumor Detection Based on Attention CNN and Time Series of Context Information
2021
Future Internet
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The proposed model is a convolutional neural network embedded with an attention mechanism of sentiment polarity and time series information. ...
The experiment results show that the proposed model introduced with features of time series and sentiment polarity is very effective for rumor detection, and can greatly reduce the number of iterations ...
Chen proposed a deep attention model based on a recurrent neural network. ...
doi:10.3390/fi13110267
fatcat:zzmbldbzqrbkhe3fzhh7piv4yy
Detecting and Analyzing Stress Based on Social Interactions in Social Networks
2018
International Journal of Computing Communications and Networking
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Sample tweets from Sina Weibo. ...
around U.S. military bases using our classifiers. ...
They proposed using the unsupervised learned Convolutional Neural Network (CNN) features to detect and recognize the texts.
Research on leveraging social interactions for social media analysis. ...
doi:10.30534/ijccn/2018/17722018
fatcat:dtrrzc4a2bd2vgisjtglxorrza
Fine-Grained Emotion Classification of Chinese Microblogs Based on Graph Convolution Networks
[article]
2019
arXiv
pre-print
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In this paper, we propose a syntax-based graph convolution network (GCN) model to enhance the understanding of diverse grammatical structures of Chinese microblogs. ...
In addition, a pooling method based on percentile is proposed to improve the accuracy of the model. ...
[14] built a character embedding with dual channel convolution neural network to comprehend the sentiment of Chinese short comments in Sina Weibo. ...
arXiv:1912.02545v1
fatcat:r5pihl2zsrf3fe4pblg53njy2i
Research on Public Environmental Perception of Emotion, Taking Haze as an Example
2021
International Journal of Environmental Research and Public Health
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This article focuses on the problem of the public perception of emotional changes, which is caused by fog and hazy weather, proposes an environmental emotion perception model, using Weibo comment data ...
Environmental problems represented by haze have become a topic that affects the harmonious ecology of human beings. The trend of this topic is on the rise. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/ijerph182212115
pmid:34831869
pmcid:PMC8624140
fatcat:qkiusyvtmbem7ka2jbp3npooyy
Detecting Stress Based on Social Interactions in Social Networks
2018
International Journal of Recent Trends in Engineering and Research
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We first define a set of stress-related textual, visual, and social attributes from various aspects, and then propose a novel hybrid model -a factor graph model combined with Convolution Neural Network ...
With the popularity of social media, people are used to sharing their daily activities and interacting with friends on social media platforms, making it feasible to leverage online social network data ...
Moti-vated by the principle of homophily, [38] incorporated social relationships to improve user-level sentiment analysis in Twitter. ...
doi:10.23883/ijrter.conf.20171201.032.rnldv
fatcat:lfsnnsqtfrf5dbclrrxg6jahby
Sentiment Analysis of online reviews based on LDA and AP-Bert model
2022
Highlights in Science, Engineering and Technology
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According to the characteristics of online comments, a BERT emotion analysis model with enhanced pooling was proposed. ...
Finally, by combining LDA extraction results and AP-Bert sentiment analysis results, the proportion matrix is obtained. ...
Online Comment Sentiment Analysis Model Based on LDA and AP-Bert
Data Preprocessing Data preprocessing is the primary task of sentiment analysis, and the validity of data directly affects the accuracy ...
doi:10.54097/hset.v1i.472
fatcat:dts27tiz7fbbjjte2ptds2vdw4
A Multichannel Model for Microbial Key Event Extraction Based on Feature Fusion and Attention Mechanism
2021
Security and Communication Networks
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In order to further mine the deep semantic information of the microbial text of public health emergencies, this paper proposes a multichannel microbial sentiment analysis model MCMF-A. ...
The results show that the F1 value of the MCMF-A sentiment analysis model reaches 90.21%, which is 9.71% and 9.14% higher than the benchmark CNN and BiLSTM models, respectively. ...
the model. e structure of the WMF-based neural network is given in Figure 3 , and the FMF-based structure is similar to it. ...
doi:10.1155/2021/7800144
fatcat:q2lmapk36nhtrk4ssxj562esc4
Man is What He Eats: A Research on Hinglish Sentiments of YouTube Cookery Channels Using Deep learning
2019
International journal of recent technology and engineering
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Our study focuses on the sentiment analysis of Hinglish comments by multi-label text classification on cookery channels of YouTube using Deep learning. ...
analysis on tests conducted during our study ...
Classification of comments with Deep neural network based on attention mechanism This paper proposes a CNN-Attention network based on Convolutional Neural Network with Attention (CNNA) mechanism in which ...
doi:10.35940/ijrte.b1153.0982s1119
fatcat:jpdo5d3b7rhzziboqq6ggszxfe
Sentimental Knowledge Graph Analysis of the COVID-19 Pandemic Based on the Official Account of Chinese Universities
2021
Electronics
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Based on sentiment analysis and text mining, entities and relationships in the theme graph of public opinion events in colleges and universities were identified, and the Neo4j graph database was established ...
By incorporating topic mining into the sentimental knowledge graph, the graph can realize functions such as the emotion retrieval of comments on university public numbers, a source search of security threats ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/electronics10232921
fatcat:7of3kgjwxjbfvaj6g4psyetilu
Sentiment Classification Algorithm based on Multi-modal Social Media Text Information
2021
IEEE Access
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This paper proposed a sentiment classification algorithm based on multi-modal social media text information. ...
INDEX TERMS UCRNN, sentiment classification, public opinion analysis, natural language processing, deep neural network, social media, multi-modal. ...
The whole model is called User attributes Convolutional and Recurrent Neural Network (UCRNN) due to the use of CNN based on user attributes and RNN based on text. ...
doi:10.1109/access.2021.3061450
fatcat:b6umtebuyrboli74rxizlybcmi
Automatic Rumor Detection on Microblogs: A Survey
[article]
2018
arXiv
pre-print
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Most rumor detection methods can be categorized in three paradigms: the hand-crafted features based classification approaches, the propagation-based approaches and the neural networks approaches. ...
Many efforts have been taken to defeat online rumors automatically by mining the rich content provided on the open network with machine learning techniques. ...
[49] proposed a set of network features based on network created via the comment providers. ...
arXiv:1807.03505v1
fatcat:kvwukm7kofhyfd3yjlajagoxce
Analysis of Public Opinion in Colleges and Universities Based on Wireless Web Crawler Technology in the Context of Artificial Intelligence
2022
Mobile Information Systems
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and CNN (Convolutional Neural Network) model. ...
As public opinion in colleges and universities becomes an increasingly important vehicle for expressing public opinion, this paper aims to explore the concepts of public opinion based on the web crawler ...
With enormous development of neural network techniques, certain data analysis based on the training sample has been well addressed. ...
doi:10.1155/2022/7745028
fatcat:5z3gacsf5zhrpjyvkn2t2cb2vm
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