Research and Design of Internet Public Opinion Analysis System

Guan, Quanlong; Ye, Saizhi; Guo-xiang, Yao; Zhang, Huanming; Wei, Linfeng; Song, Gazi; He, Kejing

doi:10.1109/ssme.2009.62

Cited by 19 publications

(8 citation statements)

References 4 publications

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“…For evaluation, we calculate the corresponding miss rate and false rate of each topic as follows: (9) The result of our algorithm is quite satisfactory, because both miss rate and false rate are low enough.…”

Section: Resultsmentioning

confidence: 99%

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An Improved Topic Detection Method for Chinese Microblog Based On Incremental Clustering

Li¹,

Meng²,

Xie³

2013

JSW

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A topic detection model based on hierarchical clustering for Chinese microblog is proposed in this paper. In order to minimize the impact of noise, we optimize the feature selection and weight computation method and use a new scoring method to filter out those topic-unrelated tweets. We also give an improved topic detection algorithm which uses a new vector distance calculation method and center vector updating method. It is shown by the experiment that this method can filter out majority of the topic-unrelated tweets and identify microblog topics accurately and efficiently. The study of microblog topic detection method can help users and service providers find out microblog hot topics dynamically.

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Section: Resultsmentioning

confidence: 99%

“…Method based on document frequency, mutual information, or information gain can be used as feature selection method to extract the most representative features [8,9,12]. In this paper, we use the feature selection method based on document frequency.…”

Section: ) Feature Selectionmentioning

confidence: 99%

An Improved Topic Detection Method for Chinese Microblog Based On Incremental Clustering

Li¹,

Meng²,

Xie³

2013

JSW

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“…• Management system, customized specially for administrators, is able to monitor the analysis results from normal users, and has rollback functionality for public opinion [8].…”

Section: A System Design Overviewmentioning

confidence: 99%

A Public Opinion Analysis System for Urban Management Information

Chen

Li²,

Shen³

et al. 2014

JCP

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Digital urban management has been a fast developing trend in modern cities. And as the development of the urban management, there are an increasing number of people finding that public opinion information is quite valuable and important for this process. So in this paper, we design a public opinion analysis system for urban management information (POASUMI), in which we implement certain functionalities like public opinion information acquisition, Chinese word segmentation, analysis and statistic of sentiment and hotspot of public opinion information. The experimental results indicate that the results generated by POASUMI can match actual condition very well, definitely providing quite valuable information for urban management.

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“…Feature selection process aims to obtain a substantial reduction of the features, whose methods based on document frequency, mutual information, or information gain could be used to reduce the number of words [8,9]. During the classification process of network text opinion, not all the words are used in the classification process.…”

Section: Reductionmentioning

confidence: 99%

Internet Public Opinion Hotspot Detection and Analysis Based on Kmeans and SVM Algorithm

Hong

2010

2010 International Conference of Information Science and Management Engineering

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Rapid progress of network arouses much attention on Internet public opinion, it is important to grasp the internet public opinion in time and understand the trends of their opinion correctly. Text mining plays a fundamental role in categorization and monitoring of internet public opinion, but internet public opinion is much more difficult than pure-text process because of their semi-structured characteristic. To address this issue, we propose a model for internet public opinion hotspot detection and analysis. Due to the text format of internet public opinion, we introduce the traditional vector space model (VSM) to express them, and then use Kmeans algorithm to perform text clustering on a corpus collected from some news website, and use SVM classifier to perform text categorization for new text opinion analysis, the result of the experiment shows that the efficiency and effectiveness of such method.

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Research and Design of Internet Public Opinion Analysis System

Cited by 19 publications

References 4 publications

An Improved Topic Detection Method for Chinese Microblog Based On Incremental Clustering

An Improved Topic Detection Method for Chinese Microblog Based On Incremental Clustering

A Public Opinion Analysis System for Urban Management Information

Internet Public Opinion Hotspot Detection and Analysis Based on Kmeans and SVM Algorithm

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