Sentiment analysis of Chinese micro-blog text based on extended sentiment dictionary

Zhang, Shunxiang; Zhang, Wei; Wang, Yin; Tao, Ling

doi:10.1016/j.future.2017.09.048

Cited by 212 publications

(111 citation statements)

References 22 publications

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“…After solving the data pre-processing and modelling problem for the unstructured short texts of social media, various common text mining applications could be utilized directly to the social media analysis, e.g., social media topic modelling, sentiment analysis, short text classification, etc. Notably, the sentiment analysis that focuses on discovering people's polarity of sentiment implied in textual words [38] could form the basis of our customer segmentation method by estimating the satisfaction degree of every online customer.…”

Section: Social Media Miningmentioning

confidence: 99%

Multifunctional Product Marketing Using Social Media Based on the Variable-Scale Clustering

Wang

Gao

2019

Teh. vjesn.

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Customers' demands have become more dynamic and complicated owing to the functional diversity and lifecycle reduction of products which pushes enterprises to identify the real-time needs of distinct customers in a superior way. Meanwhile, social media turned as an emerging channel where customers often spontaneously can express their perceptions and thoughts about products promptly. This paper examines the customer satisfaction identification and improvement problem based on social media mining. First, we proposed the public opinion sensitivity index (POSI) to uncover target customers from extensive short-textual reviews. Subsequently, we presented a customer segmentation approach based on the sentiment analysis and the variable-scale clustering (VSC). The approach is able to get several customer clusters with the same satisfaction level where customers belonging to each cluster have similar interests. Finally, customer-centered marketing strategies and customer difference marketing campaigns are planned under the shadow of customer segmentation results. The experiments illustrate that our proposed method can support marketing decision marketing in practice that enriches the intention of the current customer relationship management.

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Section: Social Media Miningmentioning

confidence: 99%

Multifunctional Product Marketing Using Social Media Based on the Variable-Scale Clustering

Wang

Gao

2019

Teh. vjesn.

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“…The semantic extraction of keyword matching method can be built by several ways. The similarity is calculated by algorithm for the semantic feature extraction of Weibo, which is studied by Zhang et al (2017Zhang et al ( , 2018. Liu et al (2015) introduced the research of the term semantic level extraction for Chinese text information processing in a specific field.…”

Section: Semantic Extraction Of Keyword Matching and Similarity Retrimentioning

confidence: 99%

A decision system based on active perception and intelligent analysis for key location security information

Chen

Cao

et al. 2019

IJCSE

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In various enterprises, the security data are manually entered by multiple security workers at different times, which can lead to disordered data in the system, and also, analysis decision files need to be manually processed. To solve these problems, this paper presents a decision system for key location security information based on active perception and intelligent analysis. First, the designed system is developed based on C/S framework. Then, a deep learning perception model is constructed. Experimental results show that this system can significantly reduce the heavy workload of security inspectors, and reduce the frequency of safety accidents.

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“…These methods calculated the similarity of the words to be estimated and the benchmark words which are pre-selected separately, then obtained the sentiment tendency of the words. Zhang et al [4] proposed a method which use of expression images combined with the emotional words to construct Chinese emotion dictionary. This method improves the accuracy of classification by constructing Bayesian Classifier, and using entropy to optimize the corpus.…”

Section: Related Workmentioning

confidence: 99%

Sentiment Analysis of Tourism Micro-blog Comments

Song¹,

Wang²

2017

dtcse

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Abstract. Recent years, an amount of tourism micro-blog comments on the Internet have become an important source of information for potential customers and to improve the service quality. These micro-blog comments do help to research tourism resources or services before making decisions. Thus, sentiment analysis of tourism micro-blog comments has become a hot issue in the field of natural language processing and text mining. We designed a system called SASTMC by using web crawler, Chinese words segmentation, emotion words dictionary and an improved TF-IDF algorithm. It enhances expression ability of sentiment information of text words. Experiments on Sina micro-blog comments datasets demonstrate that our method can do the task well.

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Sentiment analysis of Chinese micro-blog text based on extended sentiment dictionary

Cited by 212 publications

References 22 publications

Multifunctional Product Marketing Using Social Media Based on the Variable-Scale Clustering

Multifunctional Product Marketing Using Social Media Based on the Variable-Scale Clustering

A decision system based on active perception and intelligent analysis for key location security information

Sentiment Analysis of Tourism Micro-blog Comments

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