A web sentiment analysis method on fuzzy clustering for mobile social media users

Yang, Li; Geng, Xianguo; Liao, Haode

doi:10.1186/s13638-016-0626-0

Cited by 22 publications

(10 citation statements)

References 23 publications

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“…Yang et al [7] presented that fuzzy clustering theory and source database was built for micro-blog. The creator utilized HowNet, a fundamental emotion set to ascertain loads of microblog emotion words and emotional lexicon was fabricated.…”

Section: Literature Surveymentioning

confidence: 99%

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Untitled

2020

IJSC

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Opinion Mining and Sentiment Analysis in Natural Language Processing (NLP) are challenging, as they require deep understanding. Understanding involves methods that could differentiate between the facts of explicit and implicit, regular and irregular, syntactical and semantic language rules. Researches oriented towards Natural Language Processing and Sentiment Analysis have many unresolved problems like co-reference resolution, negation handling, anaphora resolution, named-entity recognition, and word-sense disambiguation. This paper is proposed to develop an Optimized Partial Ancestral Graph (O-PAG) which is capable of mining patterns in human interactions and compare it with an existing tree based pattern mining approach. The experimental results are exposed to number of frequent interactions made and execution time. Results indicate that the overall performance can reach considerable improvements on using O-PAG approach.

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Section: Literature Surveymentioning

confidence: 99%

“…It is only a discourse that characterizes open activities by the members of the gathering comparing to the present topic. Mining human interactions is significant for understanding gathering content [7].…”

Section: Literature Surveymentioning

confidence: 99%

Untitled

2020

IJSC

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“…The digital data has been clearly seen a tremendous growth. The areas of greatest interest to experts are data mining and knowledge discovery [1]. In particular, information has been developed and accumulated in a rapid and explosive manner in this century, resulting in the formation of big data, massive data and Mega data.…”

Section: Development Of Big Datamentioning

confidence: 99%

The Study of Using VGI to Analyze the Tourist Satisfaction About Taichung Jazz Festival

Lai¹

2018

ASH

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Since 2003, the Taichung Jazz Festival has become one of the major annual events regularly held in Taichung City.The number of tourists and the tourism business opportunities brought by this festival has been increasing year by year, even reaching more than 1 million participating tourists/times ever since 2015. In terms of traditional assessment methods for great events, we used to obtain analytic information such as visitor satisfaction or the number of people through questionnaires. However, different levels of issues concerned by tourists cannot be easily understood through standardized questionnaires. Due to the popularization of online platforms and smart phones, people tend to voluntarily provide some information when they are participating in an activity. Such coordinated information is namely "Volunteered geographic information" (VGI), ex. "check-in" created by anyone. People can show their positive and negative messages by expressing their words about certain places (food, landscape, etc.), which can can make up for the shortcomings of traditional questionnaires. In this study, through the API provided by Facebook and by writing a web crawler program, we downloaded a total of 46,260 comments/messages written by people during the period of the Jazz Festival. Then, by means of Chinese word segmentation and through keywords, statistical analyses were conducted on two indicators shown by these tourists regarding the Jazz Festival: 1. Satisfaction about this event: To analyze people's positive and negative evaluations of the handling of this event, as well as their feelings; 2. Suggestions for event improvements: To analyze all aspects of concrete problems and suggestions for improvements proposed by people for this event. In this study, through collecting VGI data and constructing unstructured information analysis methods, explorations were made, concerning people's intuitive feeling about Jazz Festival from a mass perspective. In addition, comparisons and analyses against traditional questionnaires were conducted. Therefore, the findings of this study can serve as a reference for future leisure activity surveys combined with VGI data analyses.

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“…With the rapid development of mobile Internet, the mobile social media services [1,2] are increasingly abundant. The mobile phone as a representative of mobile participatory sensing devices has become a part of people's daily life.…”

Section: Introductionmentioning

confidence: 99%

A reinforced collaborative filtering approach based on similarity propagation and score predication graph

Yin

Chen

Liu

et al. 2016

J Wireless Com Network

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In the era of big data, the rapid development of mobile participatory sensing devices brings the explosive expansion of data, making information overload a serious problem. In this case, a personalized recommendation system on mobile social media appears. Collaborative filtering is the most widely used approach in a recommendation system. Nevertheless, there still exist many problems, such as the serious data sparsity problem and the cold start problem. Existing approaches cannot effectively solve these problems. Most of the existing recommendation approaches are based on single information source and cannot effectively solve the cold start and data sparsity problems. In addition, some approaches proposed to solve data sparsity fail to consider the effects of users' influences and prediction order on recommendation accuracy. Accordingly, from the perspective of increasing the categories of information, the similarity propagation approach based on a heterogeneous network is proposed to ease the cold start problems by improving the similarity calculation method. In addition, to ease the data sparsity problems, we propose a hybrid collaborative filtering approach based on a score prediction graph to finish the user-item score matrix in order. Finally, we conduct validation experiments on the MovieLens dataset. Compared with five state-of-the-art approaches, our approach outperforms them in terms of the performances of mean absolute error, root-mean-square error, recall, and diversity.

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A web sentiment analysis method on fuzzy clustering for mobile social media users

Cited by 22 publications

References 23 publications

Untitled

Untitled

The Study of Using VGI to Analyze the Tourist Satisfaction About Taichung Jazz Festival

A reinforced collaborative filtering approach based on similarity propagation and score predication graph

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