• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.238-246
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• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• The Journal of Information Systems
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• v.29 no.4
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• pp.171-191
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• 2020

Purpose The study aims to compare the online review writing behavior of users in China and the United States through text mining on online reviews' text content. In particular, existing studies have verified that there are differences in online reviews between different cultures. Therefore, the purpose of this study is to compare the differences between reviews written by Chinese and American tourists by analyzing text contents of online reviews based on cultural theory. Design/methodology/approach This study collected and analyzed online review data for hotels, targeting Chinese and US tourists who visited Korea. Then, we analyzed review data through text mining like sentiment analysis and topic modeling analysis method based on previous research analysis. Findings The results showed that Chinese tourists gave higher ratings and relatively less negative ratings than American tourists. And American tourists have more negative sentiments and emotions in writing online reviews than Chinese tourists. Also, through the analysis results using topic modeling, it was confirmed that Chinese tourists mentioned more topics about the hotel location, room, and price, while American tourists mentioned more topics about hotel service. American tourists also mention more topics about hotels than Chinese tourists, indicating that American tourists tend to provide more information through online reviews.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.127-137
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• 2021

Mainland China area has been a long-term, major trade rival and partner of Taiwan, accounting for more than 40% of Taiwan's total annual trade exports, and so Sino-US trade friction is expected to have a significant impact on Taiwan's economy in the future. This study focuses on major bad news of Sino-US trade frictions and how it generates short-term shocks for Taiwan's equity market and fear sentiment. It further explores the mutual interpretation relationship between price changes such as VIX, Taiwan's stock market index, and the VIX ETF to identify which factors have information leadership as leading indicators. The study period covers 750 trading days from 2017/1/3 to 2020/1/31. This study finds that, when a policy news is announced, the stock market index falls significantly, the change in the trading price (net value) of the VIX ETF rises significantly, and the overprice rate significantly drops, but VIX does not, showing that fear sentiment exists in the Taiwan's market. The net value of the VIX ETF shows an information advantage as a leading indicator. This study suggests that, when the world's two largest economies clash over trade, the impact on Taiwan's equity market is inevitable, and that short-term fear effects will arise.

• Journal of Contemporary Eastern Asia
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• v.19 no.2
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• pp.125-147
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• 2020

On the World Refugee Day in 2017, Yao Chen, a Chinese actress, philanthropist, and social media influencer, posted messages in her Weibo in support of the United Nations Refugee Agency (UNHCR). Yet, social media users quickly interpreted this supportive message of the refugee program as encouraging people to "accept and receive refugees" (jieshou nanmin) into China. Particularly, the category of Middle Eastern refugees elicited most criticism in China's cyberspace. As the inclusion of refugees is an integral part of immigrant multiculturalism, this article examines the limits of multicultural imagination of refugees―particularly those from the Middle Eastern and North Africa―in contemporary China. I argue that the limits of multicultural imagination in contemporary China is profoundly shaped by an intricate interweaving of domestic policies and global imaginaries toward refugees. By deploying a mixed methodology, such limits are examined from legal-institutional, ideological, and sociocultural perspectives. More specifically, three interrelated aspects will be highlighted in the article: (1) the global circulation of right-wing populism imaginaries, and their entanglements with the anti-Muslim sentiments in contemporary China; (2) the current insufficiency of the legal-institutional framework regarding refugees and asylum-seekers, which needs to be contextualized in China's modern history of dealing with refugee issues; (3) population politics, the rise of Han-centric nationalism, and their constraining impact on the interpretation of historical events related to cultural diversity. In conclusion, this article also offers potential implications for further examining the different yet potentially intersected genealogies of multicultural imaginaries beyond the Middle Eastern and North African refugees in Asia.

• Journal of English Language & Literature
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• v.64 no.1
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• pp.117-133
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• 2018

This article examines Laurence Sterne's Sentimental Journey in the context of eighteenth-century British travel literature. While literary critics generally read Sterne's work as a sentimental novel, contemporary readers initially interpreted the text as a travel narrative. It is my argument that travel writing, particularly the motion entailed in travelling, plays a significant role in Sterne's critical examination of sympathy and its cultural function during this period. By narrating in great detail his narrator Yorick's mobility and the effects it has on his sentimental encounters, Sterne illustrates how sympathy is not only difficult to activate and therefore requires added stimulation in the form of motion, but also does not necessarily result in charitable actions, a moral failure that is dramatized by the literal distance Yorick maintains from the objects of his sympathy. Calling to mind the figurative distance that constitutes an integral part of Adam Smith's formulation of sympathy in The Theory of Moral Sentiments, the distance Yorick establishes through his travels indicates sympathy's failure to bridge the emotional and socioeconomic distance between individuals, thereby highlighting sympathy's limitations as a moral instrument. I argue that by using Yorick's repeated acts of sympathy to explore the problems of sentimentalism, Sterne both draws from and innovates the tradition of employing imaginary voyages to engage in philosophical inquiries.

• Journal of Contemporary Eastern Asia
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• v.19 no.2
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• pp.20-39
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• 2020

In order to overturn the exclusion of Korean schools from the newly implemented free tuition program (2010) as part of sanctions against North Korea, members of Korean schools and Japanese supporters have focused on "students' innocence" and "multicultural coexistence" as viable frameworks to explain why the students are sympathetic and legitimate subjects who deserve equal rights. Examining different political strategies employed by the Korean schools and their supporters through ethnography and media analysis, the article pays close attention to how they claim their eligibility for these rights while they negotiate state surveillance and intervention in the process. I argue that in their efforts to gain recognition as deserving and sympathetic subjects, Korean schools are trapped in what political theorist Patchen Markell calls a "permanent temptation" in pursuing "recognition." Anti-North Korea sentiments in Japan have made the desire for good recognition even more urgent among Korean school community members. The paper will demonstrate that the search for recognition unwittingly reinforces and perpetuates existing relations of subordination and state dominance over their education as it has forced the Korean schools to accept various "conditions" that would radically alter the core principle, mission, and pedagogy of Korean school education that is rooted in decolonizing theory and praxis. This paper will shed lights on dilemma of multicultural coexistence the Korean minority population faces in Japan today.

• Journal of Distribution Science
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• v.19 no.4
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• pp.25-35
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• 2021

Purpose: This study aims to analyze the factors affecting customer satisfaction in the customer reviews of omni-channel, posted on Internet blogs, cafes, and YouTube using text mining analysis. Research, data, and Methodology: In this study, frequency analysis is performed and the LDA (Latent Dirichlet Allocation) is used to analyze social big data to respond to reviewers' reaction to the recently opened omni-channel shopping reviews by L Shopping Company. Additionally, based on the topic analysis, we conduct a sentiment analysis on purchase reviews and analyze the characteristics of each topic on the positive or negative sentiments of omni-channel app users. Results: As a result of a topic analysis, four main topics are derived: delivery and events, economic value, recommendations and convenience, and product quality and brand awareness. The emotional analysis reveals that the reviewers have many positive evaluations for price policy and product promotion, but negative evaluations for app use, delivery, and product quality. Conclusions: Retailers can establish customized marketing strategies by identifying the customer's major interests through text mining analysis. Additionally, the analysis of sentiment by subject becomes an important indicator for developing products and services that customers want by identifying areas that satisfy customers and areas that evoke negative reactions.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.153-171
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• 2022

To measure economic performance, customer satisfaction indices are constructed. This study proposes an index for banking and telecom, a significant evaluative system for comparing and enhancing customer satisfaction across the industries. The study suggests and examines amendments and improvements to the prior indices and incorporates ignored indicators to propose a punier index for Pakistan. The study is a pioneer in integrating online and offline indices into a single comprehensive model. The study is enriched by the Theory of Reasoned Action and Technological Acceptance Model. A sample of 320 respondents was used. The sample was divided based on gender and marital status. To authenticate the theoretical model, PLS-SEM was applied. We discovered nine latent variables that define customer satisfaction and conclude that a single model can be utilized for e-commerce enterprises as well. The index scores are comparable to the American index for banking and the Turkish index for telecom. Multi-group analysis (MGA) was used to comprehend the differences among the groups. This reveals that customization, design, reliability, and responsiveness induce satisfaction in telecom male and married customers. For the banking industry, the difference exists in complaint handling, customization, corporate image, perceived price, reliability, responsiveness, sentiments, convenience, and security to satisfaction links, image and complaint handling to loyalty links.

• Asian Journal for Public Opinion Research
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• v.10 no.2
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• pp.102-122
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• 2022

From 2018 to 2020, the United States has repeatedly imposed sanctions on the Chinese company Huawei, which has triggered strong nationalist sentiments on the Chinese Internet. This paper is a qualitative content analysis of Zhihu netizens' views on US sanctions against Huawei to explore how anti-Western centrism influences young people's narratives. The results showed that they believe the Huawei matter is a deliberate hegemonic act by the United States because it fears the decline of its own technological status. Moreover, it is direct evidence that the United States is deliberately destroying China's economic development environment to slow down China's rise, as well as a typical manifestation of the injustice of the liberal international order. A further analysis revealed that their narrative logic is obviously influenced by the following aspects: 1) The mentality of national glory derived from comprehensive national strength leads them to believe that U.S. sanctions against Huawei are an obstacle to China's rise. 2) National humiliation leads them to view U.S. sanctions as a constant insult to China. 3) China's superiority created by China's comprehensive national strength and its scientific and technological achievements in recent years has boosted its confidence to challenge the West's absolute progress. This study examines the impact of anti-Western centrism on Chinese nationalist sentiment and offers a bottom-level perspective on the debate over the crisis of the liberal order.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2571-2586
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• 2022

The rapid popularity of government social media has generated huge amounts of text data, and the analysis of these data has gradually become the focus of digital government research. This study uses Python language to analyze the big data of the Chinese provincial government Weibo. First, this study uses a web crawler approach to collect and statistically describe over 360,000 data from 31 provincial government microblogs in China, covering the period from January 2018 to April 2022. Second, a word separation engine is constructed and these text data are analyzed using word cloud word frequencies as well as semantic relationships. Finally, the text data were analyzed for sentiment using natural language processing methods, and the text topics were studied using LDA algorithm. The results of this study show that, first, the number and scale of posts on the Chinese government Weibo have grown rapidly. Second, government Weibo has certain social attributes, and the epidemics, people's livelihood, and services have become the focus of government Weibo. Third, the contents of government Weibo account for more than 30% of negative sentiments. The classified topics show that the epidemics and epidemic prevention and control overshadowed the other topics, which inhibits the diversification of government Weibo.