Neuro-fuzzy network incorporating multiple lexicons for social sentiment analysis

Vashishtha, Srishti; Susan, Seba

doi:10.1007/s00500-021-06528-0

Cited by 12 publications

(4 citation statements)

References 51 publications

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“…To enhance the sentiment analysis effect of short texts, Yan et al proposed to mix multiple lowdimensional feature models and use fuzzy logic to build an emotion-enhanced reasoning model [57]. Vashishtha & Susan proposed an adaptive fuzzy neural network, the method uses multiple dictionaries to extract features from social media posts and perform sentiment analysis, The proposed model is called MultiLexANFIS [58], they also developed a novel unsupervised model based on fuzzy rules for the sentiment analysis problem and achieved good results on dictionaries in different domains [59]. Abdul-Jaleel et al developed a new model to address the sentiment analysis problem, the method combines the feature set extracted from emotional sentences by genetic algorithm and fuzzy logic theory to improve the feature selection of emotional sentences, the results show that it is better than ordinary keyword feature selection [60].…”

Section: A Text Classificationmentioning

confidence: 99%

Review of Survey Research in Fuzzy Approach for Text Mining

Lai

Chen

2023

IEEE Access

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Text mining has been common research field, with the emergence of Web 2.0 and the development of social software, the amount of text generated every day has increased dramatically. The texts contain a lot of valuable information, how to analysis for the information from text is very important. Therefore, many research have explored related methods and various fields of text mining, such as sentiment analysis, text clustering, text summarization, etc., However, unlike other numerical data that can be directly calculated in terms of character performance, the calculation must be performed after vector conversion, and the words may have polysemy, which provides more challenges for natural language processing. Due to the above challenges, various techniques are used for data preprocessing before analysis. In addition to the common statistical and discrete methods for text data, methods based on fuzzy logic provide another option for effective natural language analysis, Therefore, in recent years, more and more studies have added Fuzzy logic to additionally capture the context semantics of individual words to help more accurate natural language processing. This survey research discusses multiple text mining methods, The survey paper discusses multiple text mining methods, subfields and application fields, covering the literature published between 2010 and 2022, It is organized to the subtasks to be performed, the methods and natural language processing techniques used, and the application scenarios. At the end of this study, the research has provided the key point discussion and relevant suggestions for text mining combined with fuzzy logic.

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Section: A Text Classificationmentioning

confidence: 99%

Review of Survey Research in Fuzzy Approach for Text Mining

Lai

Chen

2023

IEEE Access

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“…Finally, [36] present MultiLexANFIS, an adaptive neurofuzzy inference system that integrates inputs from multiple lexicons to perform sentiment analysis on social media posts. The system classifies tweets into two classes: neutral and nonneutral, where the latter class encompasses both positive and negative polarities.…”

Section: Related Workmentioning

confidence: 99%

A Multi-Stage Machine Learning and Fuzzy Approach to Cyber-Hate Detection

et al. 2023

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Social media has revolutionized the way individuals connect and share information globally. However, the rise of these platforms has led to the proliferation of cyber-hate, which is a significant concern that has garnered attention from researchers. To combat this issue, various solutions have been proposed, utilizing Machine learning and Deep learning techniques such as Naive Bayes, Logistic Regression, Convolutional Neural Networks, and Recurrent Neural Networks. These methods rely on a mathematical approach to distinguish one class from another. However, when dealing with sentiment-oriented data, a more ''critical thinking'' perspective is needed for accurate classification, as it provides a more realistic representation of how people interpret online messages. Based on a literature review conducted to explore efficient classification techniques, this study applied two machine learning classifiers, Multinomial Naive Bayes and Logistic Regression, to four online hate datasets. The results of the classifiers were optimized using bio-inspired optimization techniques such as Particle Swarm Optimization and Genetic Algorithms, in conjunction with Fuzzy Logic, to gain a deeper understanding of the text in the datasets.

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“…Public opinion refers to the public opinion on the situation of the people in a relative social space around how social emergencies arise, change, and solve, as well as people's personal attitudes and views on government personnel and managers of related events [13]. is is also the sum of the attitudes and views expressed by the broad masses of the people towards different events and problems in society.…”

Section: Connotation and Essence Of Sports Public Opinionmentioning

confidence: 99%

Analysis of Sports Popular Trend Based on Public Opinion Mining of New Media

Xie

Han

Chen

2022

Mathematical Problems in Engineering

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As an important means of communication, sports public opinion has been paid more and more attention by the country. This article will focus on the emergency events of sports events as the main object and research and analysis of the communication function and law in the public opinion of sports events and analyzes the characteristics of public opinion communication. This paper holds that the media play the “should be” roles in different periods, such as network public opinion monitoring and early warning, public opinion information processing and interpretation, consensus builder highlighting the mainstream, and introspection of public opinion events, and there is a media role cycle in the secondary public opinion period. Spreading law of public opinion in sports events in China: trigger-conduction-outbreak mechanism. At present, the diversified interactive mode of sports events in China makes the communication environment of public opinion in sports events more and more three-dimensional and multidimensional, and it is also convenient for us to make better use of the current regulation means of public opinion in sports events. Sports network public opinion can easily go to “post-truth.” In order to strengthen the monitoring of sports public opinion and improve the ability to respond to network public opinion, using interdisciplinary thinking, this paper proposes a network public opinion guidance strategy for sports events. The experiment is aimed at the disadvantage that the trend of sports public opinion analysis and tracking is not clear. The optimization method is proposed, and the accuracy is improved by 87.5%.

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Neuro-fuzzy network incorporating multiple lexicons for social sentiment analysis

Cited by 12 publications

References 51 publications

Review of Survey Research in Fuzzy Approach for Text Mining

Review of Survey Research in Fuzzy Approach for Text Mining

A Multi-Stage Machine Learning and Fuzzy Approach to Cyber-Hate Detection

Analysis of Sports Popular Trend Based on Public Opinion Mining of New Media

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