• 대한영양사협회학술지
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• 제23권2호
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• pp.192-201
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• 2017

This study compared the Center for Children's Foodservice Management in 2012, 2014, and 2016 using big data and opinion mining. The data on the Center for Children's Foodservice Management were collected from the portal site, Naver, from January 1 to December 31 in 2012, 2014, & 2016 and analyzed by keyword frequency analysis, influx route analysis of data, polarity analysis via opinion mining, and positive and negative keyword analysis by polarity analysis. The results showed that nursery had the highest rank every year and education supported by Center for Children's Foodservice Management has increased significantly. The influx of data has increased through the influx route analysis of data. Blog and $caf\acute{e}e$, which have a considerable amount of information by the mother should be helpful for use as public relations and participation recruitment paths. By polarity analysis using opinion mining, the positive image of the Center for Children's Foodservice Management was increased. Therefore, the Center for Children's Foodservice Management was well-suited to the purpose and the interests of the people has been increasing steadily. In the near future, the Center for Children's Foodservice Management is expected have good recognition if various programs to participate with family are developed and advertised.

• 문화기술의 융합
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• 제6권1호
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• pp.111-120
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• 2020

본 연구는 소셜네트워크서비스(SNS)상의 빅데이터를 이용한 텍스트 분석기법의 응용으로서 설문 조사 기반의 여론 조사 방법론과 달리 비정형적 언어 기반의 감성 여론 조사 방법론을 제안한다. 기존의 설문 기반 여론 분석모형에 대한 대안적 방법으로 주관성에 기초한 감성 분류 모형을 이용하였다. 이를 위하여, 제20대 국회의원 선거운동 기간 중 선거 관련 실시간 트위터 자료를 수집하여 속성 기반 감성 분석을 이용한 여론의 극성과 강도에 대한 실증 분석을 수행하였다. 개별 SNS에서 사용된 단어의 극성을 분류하기 위해 Lasso 및 Ridge 회귀 모형을 이용하여 극성에 영향력이 큰 변수를 추출하였다. 추출된 변수가 극성에 미치는 긍정 및 부정에 대한 영향을 구분하고, 영향력의 강도를 분석하였다. 대중들이 소셜네트워크상에서 표현한 내용을 바탕으로 한 여론에 대한 긍정 및 부정의 감성 분석을 통해 여론의 향방을 예측하고 극성분석 모형의 정확도를 측정하여, 여론 조사 분야에서 감성 분석 방법론의 적용가능성을 확인하였다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2018년도 제30회 한글 및 한국어 정보처리 학술대회
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• pp.652-657
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• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• 대한산업공학회지
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• 제43권1호
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• pp.39-48
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• 2017

In a digital economy, users actively express their needs in many ways. Thus, many researchers analyze what users need and whether they are satisfied or not through opinion mining. In addition, they begin to find technology opportunities in heterogeneous technology fields. But they did not connect users' opinion to technology development process, only focused on natural language processing or marketing or manufacturing area. Also, heterogeneous technology fields are focused on fusion technology. Thus, this study suggests a novel approach that is based on sentimental value and can be applied to exploring technology opportunities in heterogeneous fields. Sentimental value is calculated from users' opinion through sLDA. The heterogeneous technology opportunity is explored by patent analysis. This research contributes to suggesting a hybrid methodology through patent and users' opinion. In addition, it can provide managerial efficiency by suggesting base data onto decision making.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제22권5호
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• pp.240-245
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• 2016

본 연구에서는 댓글(음식점/영화/모바일제품) 및 도메인이 없는 트위터 데이터에 대한 감성 분석을 수행하고, 각 문장에 대한 object(or aspect)와 opinion word를 추출하는 시스템을 개발하고 평가한다. 감성 분석을 수행하기 위해 Structural SVM 알고리즘과 Latent Structural SVM 알고리즘을 사용하여 비교 평가하였으며, 실험 결과 Latent Structural SVM이 더 좋은 성능을 보였으며, 구문 분석을 통해 분석된 VP, NP정보를 활용하여 object(aspect)와 opinion word를 추출할 수 있음을 보였다. 또한, 실제 서비스에 활용하기 위해 감성 탐지기를 개발하고 평가하였다.

• 산업경영시스템학회지
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• 제41권1호
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• pp.1-10
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• 2018

Current evaluation practices for IT projects suffer from several problems, which include the difficulty of self-explanation for the evaluation results and the improperly scaled scoring system. This study aims to develop a methodology of opinion mining to extract key factors for the causal relationship analysis and to assess the feasibility of quantifying evaluation scores from text comments using opinion mining based on big data analysis. The research has been performed on the domain of publicly procured IT proposal evaluations, which are managed by the National Procurement Service. Around 10,000 sets of comments and evaluation scores have been gathered, most of which are in the form of digital data but some in paper documents. Thus, more refined form of text has been prepared using various tools. From them, keywords for factors and polarity indicators have been extracted, and experts on this domain have selected some of them as the key factors and indicators. Also, those keywords have been grouped into into dimensions. Causal relationship between keyword or dimension factors and evaluation scores were analyzed based on the two research models-a keyword-based model and a dimension-based model, using the correlation analysis and the regression analysis. The results show that keyword factors such as planning, strategy, technology and PM mostly affects the evaluation result and that the keywords are more appropriate forms of factors for causal relationship analysis than the dimensions. Also, it can be asserted from the analysis that evaluation scores can be composed or calculated from the unstructured text comments using opinion mining, when a comprehensive dictionary of polarity for Korean language can be provided. This study may contribute to the area of big data-based evaluation methodology and opinion mining for IT proposal evaluation, leading to a more reliable and effective IT proposal evaluation method.

• 한국IT서비스학회지
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• 제22권3호
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• pp.101-118
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• 2023

The 'MZ generation' is accustomed to expressing their thoughts and opinions online. As a result, the role of social media in understanding the opinions and public sentiment of the MZ generation has become increasingly important. In particular, the role of social media in understanding the opinions of young people in political contexts such as policies and elections is becoming more significant. Traditionally, in such political situations, various institutions conduct opinion surveys to grasp the opinions of the people. However, existing opinion surveys have many errors and limitations in understanding the specific opinions of the entire population since they are conducted on arbitrary individuals through survey techniques. Online communities are representative social media that share the opinions of the public on specific issues such as politics, economics, and culture. Therefore, online communities are widely used as a means to supplement the limitations of traditional opinion polls. In particular, the MZ generation is familiar with online platforms, and their political support has significant influence on election results and policy decisions. With this regard, this study analyzed the relationship between the sentiment reflected in online community text data by age group on major candidates and public opinion survey support rates during the Korean presidential election for those in their 20s. The analysis showed that negative sentiments reflected in online communities by the MZ generation have a negative correlation with public opinion survey support rates. This study contributes to theory and practice by revealing a significant association between social media and public opinion polls.

• 대한가정학회지
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• 제34권5호
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• pp.223-234
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• 1996

This paper intends to examine the relationship between the consumer's enduring involvement toward clothing product, fashion innovativeness, and fashion opinion leadership. Specific purposes of the study are: 1) to identify dimensions of the enduring involvement toward clothing based on the theoretical framework; 2) to find out the effects of clothing involvement on fashion innovativeness and fashion innovativeness,m fashion opinion leadership, and demographic variables. The Likert Type questionnaires were used to measure clothing involvement, fashion innovativeness, and fashion opinion leadership. Samples of 389 women(college students, career women, housewives) living in Taegu area were analyzed by factor analysis, Pearson's correlations, t-test, and multiple regression analysis. Main results of the study are as follows: 1) Concept of the enduring involvement toward clothing is composed of five dimensions: fashion, importance, pleasure, self-expression, and perceived buying risk. 2) The clothing involvement is found to have significant influences on fashion innovativeness and fashion opinion leadership. 3) The relationships between the clothing involvement, age, educational level, and marital status are found to be statistically significant.

• Asian Journal for Public Opinion Research
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• 제7권3호
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• pp.169-198
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• 2019

This study focused on the increase in refugee-related discourse in Korean society with the recent inflow of asylum seekers to Jeju Island. The purpose of our study was to understand the trends in public opinion concerning the acceptance of refugees by analyzing the content of refugee-related video commentary on YouTube. Topic modeling was conducted to analyze the main points, context, and ideas in the comments. The results indicated that the media mainly focus on the pros and cons of refugees, restricting the refugee issue to the problem of acceptance with a narrow focus on the case of Jeju Island. Refugee acceptance was treated as overwhelmingly unacceptable in the comments. We found that commenters often used negative discourse in the comments as a device for reproducing and amplifying hate speech.

• Asia Marketing Journal
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• 제19권2호
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• pp.1-24
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• 2017

This article empirically examines the relationship between values, consumer innovativeness, online opinion leadership, and new product adoption behavior utilizing wearable technology as the overall unit of analysis. The authors analyze data collected from SNS users who possess one or more wearable devices using a structural equation modeling approach to examine the direct effects. Moreover, a bootstrapping approach is adopted to explore the indirect effects between the constructs. The results indicate that consumers who value stimulation and hedonism are more inclined to possess stronger consumer innovativeness. Consumer innovativeness also positively influences online opinion leadership, ultimately leading to the faster adoption of new products. The mediating effect of consumer innovativeness between the value stimulation and online opinion leadership is also confirmed. In addition, although consumer innovativeness has no direct effect on new product adoption behavior, it does have an indirect, mediating effect through online opinion leadership.