Analysis of Twitter for 2012 South Korea Presidential Election by Text Mining Techniques (텍스트 마이닝을 이용한 2012년 한국대선 관련 트위터 분석)
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- Journal of Intelligence and Information Systems
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- v.19 no.3
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- pp.141-156
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- 2013
Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.
When developing an android mobile application the androids intent is used as a mechanism to send messages between local equipment of androids application inner part and other applications. But the androids intent does not support sending messages via each android products intent. If there is a way to support each androids equipments to send messages, it will be easier to make non-stopping services. Non-stopping service is used when the user is using the android to do word or searching services and suddenly changes to a different android product but still maintains the progress what was currently being done without waiting the programs to be loaded. It is possible to send messages to each android products by using the socket, but the connection must be maintained stably which is the weak point. In this paper, I am suggesting a BRIF(Broadcasting Remote Intent Framework) framework to send messages to different android products. BRIF is a framework that uses the Googles C2DM service which services asynchronous transmissions to different android products. This is organized with the C2DM server, RemoteContext Api, web server and RISP(Remote Intent Service Provider) which is will be easy to be used for the developers since there are no big changes for coding compared to the intent code.
With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.
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Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.
This study was conducted twice to investigate egg purchase behavior and perception on animal welfare of Korean consumers. This study included women, who were the main decision makers and caretakers in the household, and men with one-person household. This survey was conducted with by the Computer Assisted Web Interview and Gang Survey methods. On the key considerations factor, the highest response rate was considered to be 'price', and the response rate of considering 'packing date' increased in the second survey. At a reasonable price based on 10 eggs, the response rate was the highest at 53.8% and 42.9% in both the first and second surveys and the appropriate price averages were 2,482 won and 2,132 won, respectively. The highest rate of purchase of egg consumers from 'Large Mart' followed by 'Medium sized supermarket' and 'Chain supermarket'. As for the awareness about animal welfare, the recognition ratio (73.5%) was higher in the result of the second survey than the first. The cognitive period of animal welfare was 59.0% before the insecticide egg crisis and 41.0% thereafter. Regarding whether or not they have ever seen an animal welfare certification mark and an animal welfare animal farm certification mark, 59.6% of respondents said that they saw it for the first time and 37.6% answered that they knew the animal welfare certification mark. On the animal welfare system, the 'free-range' response rate was the highest at 85.8%. The 'free-range' fit response decreased by 34.2%p, while the 'barn' and 'European type' fit response increased by 13.2%p and 24.1%p, respectively. The number of 'I have never seen' and 'I have ever eaten' responses to the recognition and eating experience of animal welfare certified eggs decreased while the number of those who answered 'Have ever seen' and 'Have eaten' increased. The answer of purchasing animal welfare certified eggs at department stores, organic farming cooperatives, and internet shopping malls was higher than that of buying conventional eggs. Of the total respondents, 92.0% were willing to purchase an animal welfare egg before the price was offered, but after offering the prices of animal welfare eggs, the intention to purchase was 62.7%, which was about 30%p lower than before. The reason for purchasing an animal welfare certified egg was the highest score of 71.0% for 'I think it is likely to be high in food safety', and 38.1% for 'I think the price is high' for lack of intention to purchase. In the sensory evaluation of animal welfare eggs, egg color and skin texture of conventional eggs were significantly higher than those of certified welfare eggs (P<0.05), and boiled eggs showed that egg whites of animal welfare certified eggs were more (P<0.05). As a result, the results of this study will contribute to the activation of the animal welfare certification system for laying hens by providing basic data on consumer awareness to animal welfare certified farmers.
Nowadays, it is common that most consumers are purchasing goods in e-stores. The e-stores eager to attract, revisit, retain, and finally convert them into loyal customers. The e-store marketers have planned and executed numerous marketing efforts. As one of the marketing activities, e-store managers attempt to build web sites that meet customers' functional and psychological needs. A wide array of studies has been done to identify factors that could affect customers' response of web sites. Majority of studies were conducted to verify technology-related and functional variables of the website which facilitate transactions and enhance customer responses such as purchase intention and website loyalty. However, there has been little research on the external cues of website and psychological variables of consumer that could have positive influences on customer response. The purpose of this study is to investigate the influence of e-store personality on e-store loyalty through mediating variables such as e-store identification, e-store trust, and e-store engagement. The authors of this study develop the model and set up the six main hypotheses and a set of sub-hypotheses based on a literature review, shown in
Purpose : To conduct a nationwide survey on the principals in radiotherapy for rectal cancer, and produce a database of Korean Patterns of Care Study. Materials and Methods : We developed web-based Patterns of Care Study system and a national survey was conducted using random sampling based on power allocation methods. Eligible patients were who had postoperative radiotherapy for rectal cancer without gross residual tumor after surgical resection and without previous history of other cancer and radiotherapy to pelvis. Data of patients were Inputted to the web based PCS system by each investigators in 19 institutions. Results : Informations on 309 patients with rectal cancer who received radiotherapy between 1998 and 1999 were collected. Male to female ratio was 59 : 41, and the most common location of tumor was lower rectum (
Recently, the CO2 emission and energy consumption have become critical global issues to decide the future of nations. Especially, the spread of IT products and the increased use of internet and web applications result in the energy consumption and CO2 emission of IT industry though information technologies drive global economic growth. EU, the United States, Japan and other developed countries are using IT related environmental regulations such as WEEE(Waste Electrical and Electronic Equipment), RoHS(Restriction of the use of Certain Hazardous Substance), REACH(Registration, Evaluation, Authorization and Restriction of CHemicals) and EuP(Energy using Product), and have established systematic green business/IT strategies to enhance the competitiveness of IT industry. For example, the Japan government proposed the "Green IT initiative" for being compatible with economic growth and environmental protection. Not only energy saving technologies but energy saving systems have been developed for accomplishing sustainable development. Korea's CO2 emission and energy consumption continuously have grown at comparatively high rates. They are related to its industrial structure depending on high energy-consuming industries such as iron and steel Industry, automotive industry, shipbuilding industry, semiconductor industry, and so on. In particular, export proportion of IT manufacturing is quite high in Korea. For example, the global market share of the semiconductor such as DRAM was about 80% in 2008. Accordingly, Korea needs to establish a systematic strategy to respond to the global environmental regulations and to maintain competitiveness in the IT industry. However, green competitiveness of Korea ranked 11th among 15 major countries and R&D budget for green technology is not large enough to develop energy-saving technologies for infrastructure and value chain of low-carbon society though that grows at high rates. Moreover, there are no concrete action plans in Korea. This research aims to deduce the priorities of the Korean green business/IT strategies to use multi attribute weighted average method. We selected a panel of 19 experts who work at the green business related firms such as HP, IBM, Fujitsu and so on, and selected six assessment indices such as the urgency of the technology development, the technology gap between Korea and the developed countries, the effect of import substitution, the spillover effect of technology, the market growth, and the export potential of the package or stand-alone products by existing literature review. We submitted questionnaires at approximately weekly intervals to them for priorities of the green business/IT strategies. The strategies broadly classify as follows. The first strategy which consists of the green business/IT policy and standardization, process and performance management and IT industry and legislative alignment relates to government's role in the green economy. The second strategy relates to IT to support environment sustainability such as the travel and ways of working management, printer output and recycling, intelligent building, printer rationalization and collaboration and connectivity. The last strategy relates to green IT systems, services and usage such as the data center consolidation and energy management, hardware recycle decommission, server and storage virtualization, device power management, and service supplier management. All the questionnaires were assessed via a five-point Likert scale ranging from "very little" to "very large." Our findings show that the IT to support environment sustainability is prior to the other strategies. In detail, the green business /IT policy and standardization is the most important in the government's role. The strategies of intelligent building and the travel and ways of working management are prior to the others for supporting environment sustainability. Finally, the strategies for the data center consolidation and energy management and server and storage virtualization have the huge influence for green IT systems, services and usage This research results the following implications. The amount of energy consumption and CO2 emissions of IT equipment including electrical business equipment will need to be clearly indicated in order to manage the effect of green business/IT strategy. And it is necessary to develop tools that measure the performance of green business/IT by each step. Additionally, intelligent building could grow up in energy-saving, growth of low carbon and related industries together. It is necessary to expand the affect of virtualization though adjusting and controlling the relationship between the management teams.
The standardization of marketing has been one of the most focused research topics in international marketing. The term "global marketing" was often used to mean an internationally standardized marketing strategy based on similarities between foreign markets. Marketing standardization was discussed only within the context of traditional physical marketplaces. Since then, the digital "marketspace" of the Internet had emerged in the 90's, and it became one of the most important drivers of the globalization process opening new opportunities for the standardization of global marketing activities. On the other hand, the opinion that a greater adoption of the Internet by customers may lead to a higher degree of customization and differentiation of products rather than standardization is also quite popular. Considering this disagreement, it is notable that comprehensive studies which focus upon the marketing standardization especially in the context of global e-commerce are missing to a high degree. On this background, the two basic research questions being addressed in this study are: (1) To what extent do companies standardize their marketing in international e-commerce? (2) Is there an impact of marketing standardization on the performance (or success) of these companies? Following research hypotheses were generated based upon literature review: H 1: Internationally engaged e-commerce firms show a growing readiness for marketing standardization. H 2: Marketing standardization exerts positive effects on the success of companies in international e-commerce. H 3: In international e-commerce, marketing mix standardization exerts a stronger positive effect on the economic as well as the non-economic success of companies than marketing process standardization. H 4: The higher the non-economic success in international e-commerce firms, the higher the economic success. The data for this research were obtained from a questionnaire survey conducted from February to April 2005. The international e-commerce companies of various industries in Germany and all subsidiaries or headquarters of foreign e-commerce companies based in Germany were included in the survey. 118 out of 801 companies responded to the questionnaire. For structural equation modelling (SEM), the Partial-Least. Squares (PLS) approach in the version PLS-Graph 3.0 was applied (Chin 1998a; 2001). All of four research hypotheses were supported by result of data analysis. The results show that companies engaged in international e-commerce standardize in particular brand name, web page design, product positioning, and the product program to a high degree. The companies intend to intensify their efforts for marketing mix standardization in the future. In addition they want to standardize their marketing processes also to a higher degree, especially within the range of information systems, corporate language and online marketing control procedures. In this study, marketing standardization exerts a positive overall impact on company performance in international e-commerce. Standardization of marketing mix exerts a stronger positive impact on the non-economic success than standardization of marketing processes, which in turn contributes slightly stronger to the economic success. Furthermore, our findings give clear support to the assumption that the non-economic success is highly relevant to the economic success of the firm in international e-commerce. The empirical findings indicate that marketing standardization is relevant to the companies' success in international e-commerce. But marketing mix and marketing process standardization contribute to the firms' economic and non-economic success in different ways. The findings indicate that companies do standardize numerous elements of their marketing mix on the Internet. This practice is in part contrary to the popular concept of a "differentiated standardization" which argues that some elements of the marketing mix should be adapted locally and others should be standardized internationally. Furthermore, the findings suggest that the overall standardization of marketing -rather than the standardization of one particular marketing mix element - is what brings about a positive overall impact on success.
. This model is composed of four paths such as dimensions of e-store personality. First of all, hypothesis 1 is partially supported because sub-hypothesis 1-1 and 1-2 are supported, whereas sub-hypothesis 1-3, 1-4, and 1-5 are rejected. Specifically, it reveals that warmth and sophistication dimensions in e-store personality have positive influence on e-store identification, however, activity, progressiveness, and strictness does not have any significant relationship on e-store identification. Secondly, hypothesis 2 was supported. Therefore, it can be said that e-store identification has a positive impact on e-store trust. Thirdly, hypothesis 3 is also supported. Hence, there is a positive relationship between e-store identification and e-store engagement. Fourthly, hypothesis 4 is supported too. e-store identification has a positive influence on e-store loyalty. Fifthly, hypothesis 5 is also accepted. This indicates that e-store trust is a precedent variable which positively affects e-store loyalty. Lastly, it reveals that e-store engagement has a positive impact on e-store loyalty. Therefore, hypothesis 6 is supported. The findings of the study imply that some dimensions of e-store personality have a positive influence on e-store identification, and that e-store identification has direct and indirect influence on e-store loyalty through e-store trust and e-store engagement positively. These results also suggest that the e-store identification in e-store personality is a precedent variable which positively affects e-store loyalty directly and indirectly through e-store trust and engagement as a mediating variable. Therefore, e-store marketers need to implement website strategy based on e-store personality, e-store identification, e-store trust, and e-store engagement to meet customers' psychological needs and enhance e-store loyalty. Finally, the limitations and future study directions based on this study are discussed.
Postoperative Radiotherapy in the Rectal Cancers Patterns of Care Study for the Years of
Development of Korean Green Business/IT Strategies Based on Priority Analysis
(한국의 그린 비즈니스/IT 실태분석을 통한 추진전략 우선순위 도출에 관한 연구)
Marketing Standardization and Firm Performance in International E.Commerce
(국제전자상무중적영소표준화화공사표현(国际电子商务中的营销标准化和公司表现))
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