• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.331-350
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• 2022

This study aims to understand topics of incivility related to COVID-19 from analyzing Twitter posts including COVID-19-related hate speech. To achieve the goal, a total of 63,802 tweets that were created between December 1st, 2019, and August 31st, 2021, covering three targets of hate speech including region and public facilities, groups of people, and religion were analyzed. Frequency analysis, dynamic topic modeling, and keyword co-occurrence network analysis were used to explore topics and keywords. 1) Results of frequency analysis revealed that hate against regions and public facilities showed a relatively increasing trend while hate against specific groups of people and religion showed a relatively decreasing trend. 2) Results of dynamic topic modeling analysis showed keywords of each of the three targets of hate speech. Keywords of the region and public facilities included "Daegu, Gyeongbuk local hate", "interregional hate", and "public facility hate"; groups of people included "China hate", "virus spreaders", and "outdoor activity sanctions"; and religion included "Shincheonji", "Christianity", "religious infection", "refusal of quarantine", and "places visited by confirmed cases". 3) Similarly, results of keyword co-occurrence network analysis revealed keywords of three targets: region and public facilities (Corona, Daegu, confirmed cases, Shincheonji, Gyeongbuk, region); specific groups of people (Coronavirus, Wuhan pneumonia, Wuhan, China, Chinese, People, Entry, Banned); and religion (Corona, Church, Daegu, confirmed cases, infection). This study attempted to grasp the public's anti-citizenship public opinion related to COVID-19 by identifying domestic COVID-19 hate targets and keywords using social media. In particular, it is meaningful to grasp public opinion on incivility topics and hate emotions expressed on social media using data mining techniques for hate-related to COVID-19, which has not been attempted in previous studies. In addition, the results of this study suggest practical implications in that they can be based on basic data for contributing to the establishment of systems and policies for cultural communication measures in preparation for the post-COVID-19 era.

• Journal of the Korean School Mathematics Society
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• v.11 no.4
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• pp.569-593
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• 2008

Since 2005 KICE-TLC has focused on the development of supporting programs for teaching consultation and pedagogical content knowledge(PCK). The purpose of this year's research was to explore types of pedagogical content knowledge(PCK, hereafter) for effective teaching mathematics topics drawn from the amended national mathematics curriculum announced in February, 2007. Based on this year's PCK research, we will develop mathematics teaching consulting program from 2009 research by field testing of developed mathematics PCK. The major source of data for this study was transcripts of audiotapes of the group discussions that took place during the regular weekly meetings where we compared and analyzed three teachers' classes. We also conducted open-ended interviews with the three teachers and collected reflective notes written by participants. This research provided teachers with an opportunity to think about what is important in the teaching of a topic and why, and to consider possibilities for future development. This research highlights the importance of teacher meetings where teachers share their expertises and insights through reflection and dialogue. By introducing the concept of PCK, examining, analyzing and modelling it in pre-service and in-service teacher education practice, we can contribute to extend teachers' professional learning. Finally, just like quality student learning, quality teaching and teacher education practices require critical reflection and careful scaffolding.

• School Mathematics
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• v.10 no.4
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• pp.489-514
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• 2008

Since 2005 KICE - TLC has focused on the development of supporting programs for teaching consultation and pedagogical content knowledge(PCK). The purpose of this year's research was to explore types of pedagogical content knowledge(PCK, hereafter) for effective teaching mathematics topics drawn from the amended national mathematics curriculum announced in February, 2007. Based on this year's PCK research, we will develop mathematics teaching consulting program from 2009 research by field testing of developed mathematics PCK. The major source of data for this study was transcripts of audiotapes of the group discussions that took place during the regular weekly meetings where we compared and analyzed three teachers' classes. We also conducted open-ended interviews with the three teachers and collected reflective notes written by participants. This research provided teachers with an opportunity to think about what is important in the teaching of a topic and why, and to consider possibilities for future development. This research highlights the importance of teacher meetings where teachers share their expertises and insights through reflection and dialogue. By introducing the concept of PCK, examining, analyzing and modelling it in pre-service and in-service teacher education practice, we can contribute to extend teachers' professional learning. Finally, just like quality student learning, quality teaching and teacher education practices require critical reflection and careful scaffolding.

• Ecology and Resilient Infrastructure
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• v.6 no.2
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• pp.89-100
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• 2019

We've reviewed existing studies on the interactions among vegetation, hydrology, and geomorphology in the stream corridors, adding one more factor of vegetation in the traditional area of hydro-geomorphology. Understanding of the interactions among those three factors is important not only academically but also practically since it is related intimately to the restoration of river corridor as well as management itself. Studies of this area started from field investigations in the latter part of the 20th century and focused on the flume experiments and then computer modelling in the 1990s and 2000s. Now, it has turned again to the field investigations of specific phenomena of the vegetative-hydrologic-geomorphologic interactions in detailed micro scales. Relevant studies in Korea, however, seem to be uncommon and far behind the international status quo in spite that practically important issues related directly to this topic have been emerged. In this study, we propose, based on the extensive literature review and authors' own knowledge and experiences, a conceptual diagram expressing the interactions among vegetation, flow (water), sediment, and geomorphology. Existing relevant studies in Korea since the 1990s are classified according to the categorization in the proposed diagrams and then briefly reviewed. Finally, considering the practical issues of riparian vegetation that have emerged recently in Korea, we propose areas of investigation needed in near future such as, among others, long-term and systematic field investigations and monitoring at multiple river corridors having different attributes on vegetative-hydrologic-geomorphologic interactions, including vegetative dynamics for succession.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.141-156
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• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.