Rating the Crisis of Online Public Opinion Using a Multi-Level Index System

Meng, Fanqi; Xiao, Xiong; Wang, Jingdong

doi:10.34028/iajit/19/4/4

Cited by 57 publications

(22 citation statements)

References 16 publications

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“…e generic data release strategy had an effect on or led to the abandonment of the environmental factors approach. As a result of the complexity of information distribution, symbolic interpretations might be confused and ambiguous [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Emergency Project Management Decision Support Algorithm for Network Public Opinion Emergencies Based on Time Series

2022

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The present study aims at proposing a time series-based network public opinion emergency (NPOE) management decision support algorithm for the problems of low decision accuracy and long decision time in traditional similar algorithms. In this proposed algorithm, after the time series data are preprocessed, the association rules of the original indicator data of network public opinion emergencies (NPOEs) are mined, the original indicator data matrix of NPOEs will be constructed, and the improved local linear embedding approach will be employed to obtain the original indicator data of NPOEs. After carrying out the preprocessing according to the preprocessing results, the objective weight of the emergency decision index is calculated through the interval value fuzzy information entropy measurement of the emergency decision index, the emergency management decision support model is constructed, and the emergency management decision support of the NPOE is realized. The simulation experiment results show that the proposed algorithm has a better effect on the decision-making effect of the management of NPOEs, and a higher decision-making efficiency is achieved.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Emergency Project Management Decision Support Algorithm for Network Public Opinion Emergencies Based on Time Series

2022

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“…Since eWOM is a condition that consumers write down and use online and does not disappear immediately; on the contrary, other consumers can still see these messages after a long period of time [24]. On the Internet, when buyers search for goods or services, consumer opinions are stored for a long time and seen by most buyers, and become the reference point for buyers when purchasing goods or services [25][26][27][28][29]. Although eWOM is different from advertising, operational writers and messages that exaggerate eWOM must also be prevented.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Application Data Mining to Capture Consumer Review Data on Booking Websites

Tsai

Chen

Lee

2022

Mobile Information Systems

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The rapid development of the Internet has led to the prevalence of big data analysis. Data mining is crucial to extracting potentially valuable information from big data and has therefore received considerable attention from researchers. Python is a common programming language used in data mining. Because of its rich database and robust capacity for scientific calculations, Python is considered an irreplaceable tool for data mining. This study adopted Python to perform a data mining analysis on visitor comments on Booking.com. The study was divided into several stages, namely, data source selection, data acquisition, data saving, data preprocessing, indexing of comments on Booking.com through the Python-based Scrapy framework, and user operation simulation through Selenium to analyze the performance of the spider program. Data mining can be used to identify useful information, which can serve as references for consumers to make purchase decisions. Extraction of data from booking sites through spider programs enables site administrators to attract more visitors. Analysis of extracted data also facilitates the elimination of misjudged comments and helps hotels improve their service quality, hardware, and personnel training.

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“…In mainland China, online public opinion in a specific period of time mainly comes from commentary articles on the WeChat platform, heated discussions on Sina Weibo, posts and comments in online communities and popular search engine information rankings. The evolution of online public opinion related to COVID-19 is relatively complex, while the development of public opinion also presents a certain “life cycle” feature [ 34 ]. The information evolution of these major online platforms can basically reflect the various processes of the dynamic evolution of online public opinion [ 35 ].…”

Section: Methodsmentioning

confidence: 99%

Using Grounded Theory to Identify Online Public Opinion in China to Improve Risk Management—The Case of COVID-19

Zhang

Sun

2022

IJERPH

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Background: During the outbreak of COVID-19, online public opinion related to the epidemic was rapidly generated and developed rapidly. If some online public opinions cannot be effectively responded to and guided, it will bring risks to social order. The government should understand how to use information on social media to grasp public demands, provide useful information in a timely manner and take countermeasures. Studying the formation mechanism of online public opinion during the outbreak can help the government make scientific decisions and improve risk management capabilities. Methods: The research selects the public opinion information of online platforms represented by WeChat, online communities, Sina Weibo and search engines, involving 75 relevant texts (1 January to 31 March 2022). According to the grounded theory method, using the QSR NVivo12 qualitative research software, the collected network texts were successively researched using open coding, axial coding and theoretical coding. Results: The structure of online public opinion during the COVID-19 epidemic was obtained. The operation mechanism of the online public opinion system about COVID-19 was mainly affected by the interaction of online public opinion objects, online public opinion subjects, online public opinion intermediaries and government forces. It was based on social facts and citizens’ appeals as the starting point, subject behaviors and prevention and control measures as the focus, government’s governance as macro-control and citizens’ evaluation as the guide. Conclusions: Scientific analysis of online public opinion is an important tool to identify and manage risks and improve the quality of government activities. Online public opinion has the function of assisting government decision-making, and the government can identify the important information reflected in it, especially the mainstream public opinion, as a reference for decision-making. By taking effective measures and properly responding to citizens’ reasonable demands, the government can prevent social risks and avoid new negative public opinions. Contributions: According to the characteristics of the basic model of online public opinion, this study provides risk mitigation suggestions for Chinese public sectors to use online public opinion, optimize epidemic prevention policies and formulate strategic measures.

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Rating the Crisis of Online Public Opinion Using a Multi-Level Index System

Cited by 57 publications

References 16 publications

[Retracted] Emergency Project Management Decision Support Algorithm for Network Public Opinion Emergencies Based on Time Series

[Retracted] Emergency Project Management Decision Support Algorithm for Network Public Opinion Emergencies Based on Time Series

Analysis of Application Data Mining to Capture Consumer Review Data on Booking Websites

Using Grounded Theory to Identify Online Public Opinion in China to Improve Risk Management—The Case of COVID-19

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