• Journal of KIISE:Computing Practices and Letters
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• v.16 no.2
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• pp.222-226
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• 2010

With the continuously increasing volume of e-commerce transactions, it is now popular to buy some products and to evaluate them on the World Wide Web. The product reviews are very useful to customers because they can make better decisions based on the indirect experiences obtainable through these reviews. However, since online shopping malls do not provide ranking results, it is not easy for users to read all the relevant review documents effectively. Product reviews include subjective and emotional opinions. Thus, the review search is different from the general web search in terms of ranking strategy. In this paper, we propose an effective method of ranking the reviews that can reflect user's intention by using opinion mining techniques. The proposed method analyzes product reviews with query words, and sentimental polarity of subjective opinions. Through diverse experiments, we show that our proposed method outperforms conventional ones.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.559-566
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• 2007

Subjective sentences express opinions, emotions, evaluations and other subjective ideas relevant to products or events. These expressions sometimes can be seen in only part of a sentence, thus extracting features from a full-sentence can degrade the performance of subjective-sentence-classification. This paper presents a method for improving the performance of a subjectivity classifier by combining two classifiers generated from the different representations of an input sentence. One representation is a sentimental phrase that represents an automatically identified subjective expression or objective expression and the other representation is a full-sentence. Each representation is used to extract modified n-grams that are composed of a word and its contextual words' polarity information. The best performance, 79.7% accuracy, 2.5% improvement, was obtained when the phrase-level classifier and the sentence-level classifier were merged.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.409-418
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• 2015

With the development of mobile devices and Internet, information exchange has actively been made through SNS and Blogs. Blogs are widely used as a space where people share their experience after their visit to tourist attractions. We propose a method of recommending associated tourist attractions based on tourists' opinions using issue analysis, association analysis, and sentimental analysis for various online reviews including news in order to help to develop tour products and policies. The result shows that north area of Chungbuk province has been selected as issue attractions, and associated attractions/keywards have been identified for given well-known attraction. Positive/negative opinion for review texts has been analyzed and user can grasp the reason for the sentiments. Multidimensional analysis technique has been integrated to derive additional sophisticated insights and various policy proposal for smart tourism.

• Korean Management Science Review
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• v.32 no.3
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• pp.91-103
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• 2015

This study recognizes that there is a correlation between the movement of the financial market and the sentimental changes of the public participating directly or indirectly in the market, and applies the relationship to investment strategies for stock market. The concerns that market participants have about the economy can be transformed to the search terms that internet users query on search engines, and search volume of a specific term over time can be understood as the economic trend of big data. Under the hypothesis that the time when the economic concerns start increasing precedes the decline in the stock market price and vice versa, this study proposes three investment strategies using casuality between price of domestic stock market and search volume from Naver trends, and verifies the hypothesis. The computational results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior in domestic stock market.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.352-359
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• 2022

The study examined a sentiment analysis based on Tweeter messages between contemporary pop musicians and classical music composers. Musicians of each genre were carefully selected for the sentiment analysis. Many opinion messages on Tweets that users have discussed were collected, and the messages were evaluated by using Naïve Bayes Classifier. The results demonstrated that users showed high positive sentiments for the two different genres. However, on average, the positive sentiment values for classical music composers are higher than for contemporary pop musicians. In addition, the rankings of the highest positive sentiments among contemporary pop musicians and classical music composers did not coincide with the popularity of the two different genres of musicians. This study will contribute to the study of future sentimental analysis between music and musicians.

• Journal of Fashion Business
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• v.13 no.6
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• pp.1-11
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• 2009

Dong Tribe is a populous nationality with brilliant civilization, they created their unique culture of costumes and accessories throughout the long river of history. And the children's costumes could be the florid feature of the splendid fashion of Dong Tribe because they reflect the sentimental tastes and consciousness of the nation. The children's costumes of Dong Tribe are classified as infants' garments and children's garibaldis by different ages, the garments are much more in kinds, fresher in colors and much complicated in shapes while comparing with the adults' garments. Furthermore, the children's hats, bibs and baby carriers are also the outstanding features in children's costumes of Dong Tribe.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.423-434
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• 2013

Since acquiring intelligence about political situations around the Korea Peninsular in a direct manner is nearly impossible, it is inevitable for the individuals or companies to rely on open and indirect data such as newspapers. However, since the contents in the newspapers are substantially unstructured and very large, conventional content analysis is time-consuming and hence very costly. Hence, this paper aims to propose a sentimental analysis method which computes daily 'peace index' from unstructured data in the newspapers. From the content analysis, words and phrases which represent the sentiment of a nation are carefully identified. To show the feasibility of the idea proposed in this paper, a prototype system with vocabulary repository about political situations was developed for estimating peace index automatically.

• American Studies
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• v.44 no.1
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• pp.137-154
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• 2021

Due to her successful novel Little Women (1869), Louisa May Alcott has generally become known as a writer of sentimental fiction. However, her thrillers demonstrate her keen insights into domestic and international issues. Alcott's so-called "left hand" shows her stances on political and historical issues in America as well as in Europe and Asia. Particularly, Alcott's supporting voice for women against social prejudices is metaphorically portrayed in "A Whisper in the Dark" (1861). Interestingly, in the story Alcott displays her knowledge of the drug trades and the cultural effects of white male colonizers exploiting other peoples and countries around the globe, which were issues that she had learned about from neighboring intellectuals and newspapers. In the paper, I examine Alcott's radical views on gender equality, chauvinistic attitudes, and transnational politics in the mid-nineteenth century.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.219-223
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• 2022

The Internet can deliver various information and services at the lowest cost without time and space constraints while targeting the world among all existing means of communication. Unlike traditional media such as TV, newspapers, and radio in the past, promotions through mobile environments allow target customers to use two-way low-cost, high-efficiency promotional strategies regardless of time and place. With the development of the Internet, social media has developed into a place to acquire information about favorite companies and their products. Social media greatly contributes to the production of text, photos, videos, and various networks, and has expanded global communication and communication media through the interaction and sharing of various information. In addition, through social media, users can communicate in various ways, reveal themselves, and share and exchange information such as knowledge and personal thoughts. In line with these changes, corporate marketers and sellers are striving to provide consumers with appropriate information more quickly. We aims to find out about social media marketing strategies useful for companies.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.3
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• pp.291-299
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• 2013

Most sentiment analysis systems count the number of occurrences of sentiment expressions in a text, and evaluate the text by summing polarity values of extracted sentiment expressions. However, linguistic contexts of the expressions should be taken into account in order to analyze sentimental orientation of the text meticulously. Korean auxiliary predicates affect meaning of the main verb or adjective in some ways while attached to it in their usage. In this paper, we introduce a new approach that handles Korean auxiliary predicates in the light of sentiment analysis. We classify the auxiliary predicates according to their strength of impact on sentiment polarity values. We also define compositional rules of auxiliary predicates to update polarity values when the predicates appear along with sentiment expressions. This approach is implemented to a sentiment analysis system to extract opinions about a specific individual from review documents which were collected from various web sites. An experimental result shows approximately 72.6% precision and 52.7% recall for correctly detecting sentiment expressions from a text.