• Journal of Information Technology Services
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• v.22 no.3
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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.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.53-69
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• 2006

Recently as the Internet services become popular, the number of practical approaches to tackle social problems by using computers is increasing rapidly. One of the typical problems is the surveying system that handles a large amount of various data and thus requires much effort in time and manpower. As the necessity of the computerized surveying system is increased, there have been many tries to develop the surveying system based on the web or standalone software for public opinion collection, market research, and so on. In this paper, we design and implement a respondent based real-time surveying system using XML and QCL in order to efficiently process a various style of questionaries.

• The Korean Journal of Archival Studies
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• no.55
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• pp.235-273
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• 2018

The National September 11 Memorial is the institution that collects, assesses, arranges, uses, exhibits, and preserves collections related to the terror attack on September 11, 2001 (9/11), and the explosion incident at the World Trade Center (WTC) on February 26, 1996. After the 9/11 incident, various groups, including the LMDC and the PANYNJ, have participated in the establishment of this organization. Since its initial establishment, the necessity for memorial institutions and detailed characteristics had been discussed in meetings to gather citizens' opinions. Furthermore, the enactment of the 9/11 Memorial Act has secured the institution's stable operation and management. To properly manage disaster-related collections, a just agreement among the citizens and the government should be made to arrive at rational decision-making. This instution can provide answers regarding those ways. Moreover, managing disaster-related collections should be discussed as an important means of remembering, preserving memories, educating, revealing the truth, and preparing academic information and sources. As a result, collaborative governance in records management after a disaster is expected.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.3
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• pp.92-102
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• 2018

The purpose of this study is to investigate if subjective well-being could be improved by visiting urban forests near residential areas. Because visiting an urban forest is not an intense positive experience, this research is focused on frequency of affective experience rather than intensity. The independent variables are number of visits and length of stay. The dependent variables are positive affect, negative affect, and life satisfaction. A polling agency was employed to select 600 respondents by quota sampling, and data was collected by online survey. The results of ANOVA showed that there was no interaction between the number of visits and length of stay. Regardless of the number of visits, the subjective well-being of visitors of urban forests was enhanced: (a) positive affect of respondents who had visited in the past 2 weeks was increased while negative affect was decreased, and (b) life satisfaction for those who had visited at least 1 time per month was enhanced among usual visitors. The stay of length, however, had little effect on the increase or decrease of these three variables. The results of this study support the existing theory that one could reset their genetically determined happiness set point to a higher level by participating in intentional activities such as visiting urban forests that offer ways to achieve long-lasting changes in well-being. This means that it would be a valuable government investment to construct and maintain urban forests for improving citizens' welfare. A few comments were suggested regarding data collection and inclusion of influencing variables to make future subjective well-being studies more reliable.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.3
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• pp.25-34
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• 2014

The purposes of this study are two folds: (a) to identify the influences of tourism on subjective well-being, and (b) to understand the roles of travel motivation, constraint and personal value in subjective well-being. A polling agency was employed to select 500 respondents by quota sampling, and data was collected by online survey. ANOVA and regression results showed that tourism participants, compared to the non-participants, have a tendency to select tourism as a mean to enhance their subjective well-being because they are more self-motivated people. Their high motivation to take a trip lead to set up their feasible goals to achieve by the tourism experience and their relatively few constraints help them to have trip easily. The people's satisfaction in tourism contributes to the satisfaction in his/her leisure life, which in turn contributes to his/her subjective well-being. It is also revealed that tourism participation and subjective income level are significant variables affecting subjective well-being, which explain 21.1 percent of the variance. The research suggests various managerial implications to reduce constraints and several ideas for future researches.

• Korean journal of communication and information
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• v.48
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• pp.109-134
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• 2009

This study explores the political parody, which has become an active art form in order to express Korean Internet users' political practices, especially, during the politically turbulent periods from the presidential election of 2003 to the recent candlelight vigil protest of 2008. This study investigates the rise and fall of a parody culture by online users from the mid-2000s, and also examines aesthetical aspects of parodic artworks relying on amateurism culminated in 2004. Specifically, the current study questions an aesthetical lack shown in 'appropriation', by which most of the online users simply produce imitations of original image. This study rather notes 'photomontage' as an aesthetic prototype, the political aesthetics made by John Heartfield, through which this study intends to observe how his aesthetical legacy of political art could be realized in the contemporary form of political parodies produced by online users. The present paper concludes that online users' political participations in producing critical works of art could allow us to negate the dichotomy between the elite and the mass, professional artists and amateur parodists, and a radical politics and the politics of style.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.345-351
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• 2020

Administrative agencies today are paying keen attention to big data analysis to improve their policy responsiveness. Of all the big data, news articles can be used to understand public opinion regarding policy and policy issues. The amount of news output has increased rapidly because of the emergence of new online media outlets, which calls for the use of automated bots or automatic document classification tools. There are, however, limits to the automatic collection of news articles related to specific agencies or departments based on the existing news article categories and keyword search queries. Thus, this paper proposes a method to process articles using classification glossaries that take into account each agency's different work features. To this end, classification glossaries were developed by extracting the work features of different departments using Word2Vec and topic modeling techniques from news articles related to different agencies. As a result, the automatic classification of newspaper articles for each department yielded approximately 71% accuracy. This study is meaningful in making academic and practical contributions because it presents a method of extracting the work features for each department, and it is an unsupervised learning-based automatic classification method for automatically classifying news articles relevant to each agency.

• Korean Journal of Legislative Studies
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• v.24 no.1
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• pp.135-170
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• 2018

The recent success of populist parties and candidates in the US and European countries leads to a massive amount of empirical research on populism, a deviant form of representative democracy. Much ink has been spilled to define populism and to identify the causes of its rise and continued success in democratic political system. However, little is known about populist attitudes of individual voters. Using a large-scale online survey fielded in the context of the South Korean presidential election in 2017, this study examines (1) what determines populist attitudes of South Korean voters and (2) how populist attitudes are associated with evaluations of political parties, candidates, and political issues. Statistical analysis reveals that people high on populism are more likely to support an underdog left-wing political party and its presidential candidate, and are less likely to support policies implemented or proposed under the auspices of the Park Geun-hye administration. These findings do not necessarily suggest the inherent affinity between populism and left-wing ideology; rather, it implies populist attitudes happened to appear in 2017, in reactions to lack of confidence in the previous government.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.225-232
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• 2021

Nowadays, opinion leaders influence the formation of public opinion on various issues in social network services. There has been a lack of research on the personal characteristics that inspire users to interact with opinion leaders and show intent to act. This paper verifies how the disposition of Facebook users' self-identity affects the quasi-social interaction with opinion leaders on Facebook and the intention to share information. As the perception and behavior of users on social media platforms differ depending on the type of issue, an online survey was conducted by classifying issue types into life culture and political sectors. Research found that personal identity had a significant positive effect on quasi-social interactions in the life culture and politics sectors, while group identity negatively affected quasi-social interactions. In addition, the intention to share information was confirmed to have a significant effect only in the life and culture areas of self-identity (social and group identity). Quasi-social interaction was confirmed to have a significant positive effect on all issue areas. The results of this study suggest the need to consider variations in opinion leader marketing strategies based on the types of self-identity of Facebook users in the future. In addition, the study shows that raising the level of quasi-social interaction at the corporate level without distinction of issue types can lead to effective results.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.