• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.169-176
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• 2020

Business going concern is an important issue to be addressed since it determines how companies will survive. One indicator of the going concern problem is going concern opinion. The going concern opinion is a result of evaluation of auditors on going concern assumption of financial reporting. This research aims to examine the effect of opinion shopping, prior opinion, audit quality, and financial condition on going concern opinion. Research sample consists of 80 listed manufacturing companies on the Indonesian Stock Exchange surveyed between 2013 and 2017. Analysis data uses logistic regression. Based on the result, prior opinion affects going concern opinion, while opinion shopping, audit quality, and financial condition have no effect on going concern opinion. The significant effect of prior opinion on going concern opinion indicates that auditors consider the evaluation of the previous condition of companies' concern problematic since going concern is hard to be solved in a short-term period. This research provides recommendations for companies to increase their business ability so going concern problem can be avoided. This research also suggests to auditors to consider prior opinion to issue current opinion since previous companies' condition can be used as a general picture to initiate the auditing process.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.310-322
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• 2023

Although the network environment is gradually improving, the virtual nature of the network is still the same fact, which has brought a great influence on the supervision of Weibo network public opinion dissemination. In order to reduce this influence, the user information of Weibo network public opinion dissemination is studied by using Python technology. Specifically, the 2019 "Ethiopian air crash" event was taken as the research subject, the relevant data were collected by using Python technology, and the data from March 10, 2019 to June 20, 2019 were constructed by using the implicit Dirichlet distribution topic model and the naive Bayes classifier. The Weibo network public opinion user identity graph model under the "Ethiopian air crash" on June 20 found that the public opinion users of ordinary netizens accounted for the highest proportion and were easily influenced by media public opinion users. This influence is not limited to ordinary netizens. Public opinion users have an influence on other types of public opinion users. That is to say, in the network public opinion space of the "Ethiopian air crash," media public opinion users play an important role in the dissemination of network public opinion information. This research can lay a foundation for the classification and identification of user identity information types under different public opinion life cycles. Future research can start from the supervision of public opinion and the type of user identity to improve the scientific management and control of user information dissemination through Weibo network public opinion.

• Korean journal of communication and information
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• v.42
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• pp.168-204
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• 2008

According to the spiral of silence theory, perception of opinion climates influences willingness to express one's opinion. This study examines the relationship between opinion perception and opinion expression in different regions and issues. The results show that one's opinion and the intensity of opinion affect the expression of opinion about national and regional issues in Busan and Gwangju. People who perceive their opinions as majority are more willing to express theirs about national and regional issues in Gwangju, but not in Busan. Regression analyses show that perceived public opinion does not predict the expression of opinion in both cities. People who perceive their opinions more favorable about regional issue have lower intention to express their opinions than people who perceive their opinions same as others'. In summary, one's opinion and perception bias about controversial issues are important variables influencing expression of opinion, and the influence of perceived public opinion on opinion expression varies in different regions with different distribution of public opinion. This study found 'new hardcores' who perceive their own opinion as minor but more valuable and have the intention to speak out in places more difficult to express.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.111-119
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• 2016

In recent years, the opinion analysis is one of the key research fronts of any domain. Opinion target extraction is an essential process of opinion analysis. Target is usually referred to noun or noun phrase in an entity which is deliberated by the opinion holder. Extraction of opinion target facilitates the opinion analysis more precisely and in addition helps to identify the opinion polarity i.e. users can perceive opinion in detail of a target including all its features. One of the most commonly employed algorithms is a sequence labeling algorithm also called Conditional Random Fields. In present article, recent opinion target extraction approaches are reviewed based on sequence labeling algorithm and it features combinations by analyzing and comparing these approaches. The good selection of features combinations will in some way give a good or better accuracy result. Features combinations are an essential process that can be used to identify and remove unneeded, irrelevant and redundant attributes from data that do not contribute to the accuracy of a predictive model or may in fact decrease the accuracy of the model. Hence, in general this review eventually leads to the contribution for the opinion analysis approach and assist researcher for the opinion target extraction in particular.

• Asian Journal for Public Opinion Research
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• v.8 no.1
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• pp.22-40
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• 2020

With social media booming, newspapers are facing an enormous challenge, and some have even had to exit the market. Likewise, their role as a main force of public opinion guidance in China has also been challenged. They have lost their vantage ground. The present study conducted a case study on one well-known Chinese online public opinion event. Through analyzing the newspapers' role played in different public opinion development stages, this study displayed how Chinese newspapers worked together and successfully guided online public opinion in that case. The newspapers' advantages in guiding public opinion and suggestions as to how newspapers can survive and guide public opinion in the new media era are put forward in the final section.

• International Journal of Contents
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• v.14 no.4
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• pp.10-17
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• 2018

China media environment has drastically changed leading to the an inevitable change of public opinion ecology. Empirical studies have focused less on public opinion guidance, which forms an important component of the government officials' media literacy. This study applied quantitative method in the investigation of media literacy in China. Ideally, media literacy is measured from media cognition, media contact, media usage under the view of public opinion guidance. The findings reveal that the existing problem on 1) incorrect media cognition and public opinion guidance; 2) insufficient contact of personal social media 3) improper tendencies in the use of media to guide the public opinion, especially, on confidential information. Consequently, in order to improve media literacy in China government officials, enhancement of their basic knowledge on news diffusion and public opinion is necessary. Secondly, to effectively deal with "agenda settings", it is important for the government to consider the provision of valuable information and platforms to effectively spread information. So they need to learn how to personally and officially use social media platforms such as Weiboa and Wechat. This ensures they have maximized their potential to acquire valuable information and spread them on valuable platforms. Thirdly, government officials should be able to analyze and understand public opinion trends for official and personal use. Finally, they should understand the development of public opinion and the how online public opinion laws are formed and the target group.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.21-29
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• 2010

Opinion retrieval which searches the opinions expressed in documents by users cannot outperform significantly yet traditional topical retrieval which searches the facts. Therefore, the focus of this paper is to identify the statistical characteristics which can be applied to opinion retrieval by comparing and analyzing the term statistics of opinion and non-opinion documents in the blog domain. The TREC Blogs06 collection and 150 TREC topics are used in the experiments. The difference between term probability distributions in opinion documents is measured by JS divergence, and the difference according to the topic types and topic domains is also investigated. Moreover, the term probabilities of opinion terms are analyzed comparatively. The main findings of this study include the following: it is necessary to consider the topic-specific characteristics for the opinion detection; it is effective to extract positive and negative opinion terms according to the topics; the topic types are complementary to the topic domains; and special attention has to be given to the usage of the positive opinion terms.

• Korean journal of communication and information
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• v.39
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• pp.178-223
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• 2007

The polarization of public opinion by regionalism is one of biggest problems in Korean society. This study attempts to examine the polarization of public opinion between two typical cities representing regionalism and explore the factors influencing on the polarization. The results show that the polarization of public opinion is based on the perceived public opinion rather than the real public opinion. The polarization of public opinion is greater with regional issue than national issue. In general, citizens of Pusan have a conservative bias in estimating other Pusan citizens' opinion and a liberal bias in estimating Gwangju citizens' opinion, whereas citizens of Gwangju have a looking-glass perception in estimating other Gwangju citizens' opinion and a conservative bias in estimating Pusan citizens' opinion. There are no significant differences of the real public opinion and the perceived opinion across three generations. But within each generation, the tendency of public opinion polarization is found between regions and is not shown to change over generations. Regression analyses show that individual's opinion and region are highly predictable variables that explain the perceived public opinion and the perception bias such as false consensus and pluralistic ignorance.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.39-47
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• 2012

The opinion of user on a certain product is expressed in positive/negative sentiments for specific features of it. In some cases, they are expressed for a holistic part of homogeneous specific features, or expressed for product itself. Therefore, in the area of opinion mining, name of opinion features to be extracted are specific feature names, holonyms for theses specific features, and product names. However, when the opinion target is described with product name or holonym, sometimes it may not match feature name of opinion sentence to true opinion target intended by the reviewer. In this paper, we present a method to extract opinion targets from opinion sentences. Most importantly, we propose a method to extract true target from the feature names mismatched to a intended target. First, we extract candidate opinion pairs using dependency relation between words, and then select feature names frequently mismatched to opinion target. Each selected opinion feature name is replaced to a specific feature intended by the reviewer. Finally, in order to extract relevant opinion features from the whole candidate opinion pairs including modified opinion feature names, candidate opinion pairs are rearranged by the order of user's interest.

• Journal of the Korean Society for information Management
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• v.27 no.3
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• pp.227-239
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• 2010

Opinion retrieval is to retrieve items which are relevant to the user information need topically and include opinion about the topic. This paper aims to find a method to represent user information need for effective opinion retrieval and to analyze the combination methods for opinion features through various experiments. The experiments are carried out in the inference network framework using the Blogs06 collection and 100 TREC test topics. The results show that our suggested representation method based on hidden 'opinion' concept is effective, and the compact model with very small opinion lexicon shows the comparable performance to the previous model on the same test data set.