• Title/Summary/Keyword: Predict election results

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Analysis of Twitter for 2012 South Korea Presidential Election by Text Mining Techniques (텍스트 마이닝을 이용한 2012년 한국대선 관련 트위터 분석)

  • Bae, Jung-Hwan;Son, Ji-Eun;Song, Min
    • 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.

A Study on Use Behavior and Demand Forecasting of Legislative Information Service for the Member of the National Assembly (국회의원의 입법정보 이용행태와 수요예측에 관한 연구)

  • Cho, Jeong-Kwon;Bae, Kyung-Jae
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.3
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    • pp.155-169
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    • 2016
  • The purpose of this study is to find a policy and to predict the needs of legislative information service of the 20th National Assembly. For this purpose, It is critical to understand the use behavior of legislative information service according to the attribute for the member of the 19th National Assembly. Thus, this study examined the results of reference service of National Assembly Library of Korea using the politics attribute and the relation attribute as independent variables for the member of the National Assembly in the First Half of the 19th National Assembly. Consequently, there were meaningful differences in the use of legislative information service between users by party affiliation, method of an election and introversion. Also, the increased demand of legislative information service was predicted in that the 20th National Assembly is the status of the opposition majority and the three major parties.

Instructors' Perceptions of Legislation of the Amendments of Higher Education Law and Direction for Revision -Focusing on the Instructors in the Fields of Humanities/Social Science/Education- (강사법 제정 및 개정 방향에 대한 강사들의 인식: 인문/사회/교육계열 강사들을 중심으로)

  • Kim, Jungsook
    • (The)Korea Educational Review
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    • v.22 no.1
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    • pp.25-51
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    • 2016
  • This study was designed to analyze instructors's perceptions on legislation of the amendments of the Higher Education Law in 2011 and discuss some issues related to direction for revision henceforth. This study explored two research questions. First, how do instructors perceive the legislation of the amendments of Higher Education Law? Second, how do they think the directions for the revision of the law? To complete this task, the author conducted in-depth interviews with 16 interviewees; 13 instructors and 3 specialists of the higher education. As a result of in-depth interviews, the author found that instructors perceive the law as condescending law or election-based law even though they recognize the significance of the law. They predict that the law can increase non-tenure track faculty members. In addition, they emphasize the law should be revised to improve the instructors' labor condition substantially, for instance increase of the teaching pay and employment stabilization. However, instructors' opinions on the law itself and its revision direction are divided according to their age and major. Based on the results of this study, I discussed some potential issues of the revision of the law and suggested improvement plans.