• Journal of Information Science Theory and Practice
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• 제9권1호
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• pp.35-53
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• 2021

The study reported in this paper aimed to evaluate the topics and opinions of COVID-19 discussion found on Twitter. It performed topic modeling and sentiment analysis of tweets posted during the COVID-19 outbreak, and compared these results over space and time. In addition, by covering a more recent and a longer period of the pandemic timeline, several patterns not previously reported in the literature were revealed. Author-pooled Latent Dirichlet Allocation (LDA) was used to generate twenty topics that discuss different aspects related to the pandemic. Time-series analysis of the distribution of tweets over topics was performed to explore how the discussion on each topic changed over time, and the potential reasons behind the change. In addition, spatial analysis of topics was performed by comparing the percentage of tweets in each topic among top tweeting countries. Afterward, sentiment analysis of tweets was performed at both temporal and spatial levels. Our intention was to analyze how the sentiment differs between countries and in response to certain events. The performance of the topic model was assessed by being compared with other alternative topic modeling techniques. The topic coherence was measured for the different techniques while changing the number of topics. Results showed that the pooling by author before performing LDA significantly improved the produced topic models.

• Journal of Information Science Theory and Practice
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• 제10권3호
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• pp.40-56
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• 2022

This paper aims to implement a topic modeling technique for extracting the topics of online discussions among library professionals in India. Topic modeling is the established text mining technique popularly used for modeling text data from Twitter, Facebook, Yelp, and other social media platforms. The present study modeled the online discussions of Library and Information Science (LIS) professionals posted on Lis Links. The text data of these posts was extracted using a program written in R using the package "rvest." The data was pre-processed to remove blank posts, posts having text in non-English fonts, punctuation, URLs, emails, etc. Topic modeling with the Latent Dirichlet Allocation algorithm was applied to the pre-processed corpus to identify each topic associated with the posts. The frequency analysis of the occurrence of words in the text corpus was calculated. The results found that the most frequent words included: library, information, university, librarian, book, professional, science, research, paper, question, answer, and management. This shows that the LIS professionals actively discussed exams, research, and library operations on the forum of Lis Links. The study categorized the online discussions on Lis Links into ten topics, i.e. "LIS Recruitment," "LIS Issues," "Other Discussion," "LIS Education," "LIS Research," "LIS Exams," "General Information related to Library," "LIS Admission," "Library and Professional Activities," and "Information Communication Technology (ICT)." It was found that the majority of the posts belonged to "LIS Exam," followed by "Other Discussions" and "General Information related to the Library."

• 한국멀티미디어학회논문지
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• 제23권4호
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• pp.595-602
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• 2020

We propose a generative probabilistic model with Dirichlet prior distribution for topic modeling and text similarity analysis. It assigns a topic and calculates text correlation between documents within a corpus. It also provides posterior probabilities that are assigned to each topic of a document based on the prior distribution in the corpus. We then present a Gibbs sampling algorithm for inference about the posterior distribution and compute text correlation among 50 abstracts from the papers published by IEEE. We also conduct a supervised learning to set a benchmark that justifies the performance of the LDA (Latent Dirichlet Allocation). The experiments show that the accuracy for topic assignment to a certain document is 76% for LDA. The results for supervised learning show the accuracy of 61%, the precision of 93% and the f1-score of 96%. A discussion for experimental results indicates a thorough justification based on probabilities, distributions, evaluation metrics and correlation coefficients with respect to topic assignment.

• 음성과학
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• 제13권2호
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• pp.87-105
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• 2006

Many researchers have studied the relationship between the information structure and intonation. Arguments about the relations between the information structure and intonation researched so far can be summarized as follows: the intonation of topic and focus in English information structure is represented as i) a pitch accent, ii) a tune (a pitch accent + an edge tone), or iii) a boundary tone. The purpose of this paper is to study various informational patterns of the topic in English information structure, using real TV discussion data. In this paper, the topic is classified as contrastive topics and non-contrastive topics, based on contrastiveness. The results show that the intonation of the topic in English information structure is implemented as a pitch accent, neither a tune nor a boundary tone. Of the non-contrastive topics, while anaphoric determinative NP topics (Lnc, Lncd) are mainly represented as a H* pitch accent, the pronoun topic(Lp) does not have a pitch accent. Of contrastive topics, while the semantically focused topic(Lci) is mainly represented as a H* pitch accent, the contrastively focused topic(Lcc) is represented as both H* and L+H* pitch accents. It shows that it is not always true that the topic or focus to have the meaning of contrast is represented as a L+H* pitch accent as argued in the previous researches.

• 한국과학교육학회지
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• 제30권5호
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• pp.533-543
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• 2010

이 연구는 자유주제 과학탐구 과정에서 일어나는 인지수준 향상 정도 및 탐구단계별 상호작용을 분석함으로써, 자유주제 과학탐구에 대한 질적 이해를 돕고자 하였다. 자유주제 과학탐구는 인지수준이 과도기(2B/3A)이고, 학습동기수준이 심층학습형, 심층능력형인 학생들의 탐구능력 신장에 긍정적인 효과가 있었다. 또한 학생들은 탐구과정 중 주제 및 가설설정단계에서 어려움을 겪으며, 자유탐구가 진행됨에 따라 논의의 기술은 증가하나, 상호작용의 질적 향상은 쉽게 나타나지 않음을 알 수 있었다. 심층학습형은 모둠 내에서 사고의 정교화를 촉진하는 역할을 하고 있었다. 심층능력형은 가장 주도적으로 상호작용에 참여하여 논의를 이끄나, 탐구결과에 대한 집착으로 과정적 측면을 소홀히 하는 경향이 있었다. 그리고 피상능력형은 하위수준의 상호작용이 많아서 논의를 심화시키지 못하나, 자유탐구가 진행됨에 따라 점차 상위수준의 상호작용이 증가하는 긍정적인 변화를 보였다. 이 연구로부터 자유주제 과학탐구 활동의 특성 및 자유주제 과학탐구 활동의 진행과 모둠구성에 대한 시사점을 얻을 수 있었으며, 이에 대해 논하였다.

• 수산해양교육연구
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• 제27권1호
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• pp.108-114
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• 2015

The purpose of this study is to find the relationships among communication competency, social network centrality(trust centrality and knowledge sharing centrality), discussion performance, and online boarding activity in the team based learning situation. For investigating this topic, 44 students are participated in the classes of educational technology. In order to find out the relationships among communication competency, social network centrality, discussion performance, and online boarding activity, compared t-test and path analysis are used. Followings are the results of the research: (a) Communication competency is improved significantly after team based learning. (b) Trust centrality effects significantly on the knowledge sharing centrality. (c) Knowledge sharing effects significantly on discussion performance. (d) Trust centrality effects on the online boarding activity in the team based learning.

• 말소리와 음성과학
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• 제1권2호
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• pp.119-128
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• 2009

Many researchers have argued about the relationship between information structure and intonation. Their results can be summarized in three main points: the intonation of topic and focus in English information structures is implemented as i) a pitch accent, ii) a tune (a pitch accent + (an) edge tone(s)), or iii) a boundary tone. The purpose of this paper is to study various intonational patterns of topic and focus in English information structures, using natural conversations. In this paper, the types of topics and foci are divided, based on contrastiveness. The topics are classified as five non-contrastive and four contrastive topics. The foci are classified as neutral focus, informational focus, and contrastive focus. The results show that the intonation of the topic in English information structures is mainly implemented as a pitch accent, except for the type of the pronoun topic (Lp) which is not implemented as a pitch accent or a tune. However, the intonation of the focus is implemented as a tune in the neutral focus (Fn) and as a pitch accent or a tune in the informational focus (Fi) and the contrastive focus (Fe). In our discussion and conclusion, we suggest that it is not always true that for the meaning of contrast, the topic or the focus is represented as a $L+H^{\ast}$ pitch accent, which has been the main contrastive intonation from earlier studies.

• Educational Technology International
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• 제25권1호
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• pp.1-25
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• 2024

This study aims to analyze the impact of learners' usability perceptions of topic modeling-based visual feedback and generative AI interpretation on reflection levels in online discussions. To achieve this, we asked 17 students in the Department of Korean language education to conduct an online discussion. Text data generated from online discussions were analyzed using LDA topic modeling to extract five clusters of related words, or topics. These topics were then visualized in a network format, and interpretive feedback was constructed through generative AI. The feedback was presented on a website and rated highly for usability, with learners valuing its information usefulness. Furthermore, an analysis using the non-parametric Mann-Whitney U test based on levels of usability perception revealed that the group with higher perceived usability demonstrated higher levels of reflection. This suggests that well-designed and user-friendly visual feedback can significantly promote deeper reflection and engagement in online discussions. The integration of topic modeling and generative AI can enhance visual feedback in online discussions, reinforcing the efficacy of such feedback in learning. The research highlights the educational significance of these design strategies and clears a path for innovation.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.35-41
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• 1996

This paper presents a short introduction to fuzzy measures and fuzzy integrals for providing an useful understanding of articles related on fuzzy measure theory and its applications. A brief overview of the basic concepts of systems, models, uncertainty, fuzzy measures and fuzzy integrals is provided. And terminology and notation frequently used in the discussion on the topic are introduced.

• 한국과학교육학회지
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• 제24권3호
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• pp.638-645
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• 2004

본 연구에서는 학생들의 창의적 문제해결력과 비판적 사고력을 함양하기 위한 프로그램으로 온라인 물리탐구토론 학습체제를 개발하여, 온라인 물리탐구토론에 참여한 학생들의 상호작용 유형을 단위토론에서의 참여자 수, 다중토론장의 형성, 대화의 이동을 중심으로 구분하여 개인간 상호작용 유형, 일대일 참여의 상호작용 유형, 다중참여로 인한 일대다 상호작용 유형, 다대다 상호작용 유형등으로 분류하였다. 이는 사이버 상에서 벌어지는 학생들의 참여구조와 상호작용 양상을 파악할 수 있어 온라인을 통한 교육의 방향에 좋은 정보를 제공해 줄 수 있을 것으로 기대한다.