• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.87-97
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• 2019

Reaction of people is importantly considered about specific case as a social network service grows. In the previous research on analysis of social network service, they predicted tendency of interesting topic by giving scores to sentences written by user. Based on previous study we proceeded research of sentiment analysis for social network service's sentences, which predict the result as positive or negative for movie reviews. In this study, we used movie review to get high accuracy. We classify the movie review into positive or negative based on the score for learning. Also, we performed embedding and morpheme analysis on movie review. We could predict learning result as positive or negative with a number 0 and 1 by applying the model based on learning result to social network service. Experimental result show accuracy of about 80% in predicting sentence as positive or negative.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.98-105
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• 2022

This study's purpose is to suggest a pedagogical method based on using animated movie in liberal arts English classes and to examine the direction that using animated movie as learning material should take. To this end, in this study, the content understanding and expression concentration stages using animated movie are presented. After students learned in class through animated movie, two tests were conducted to investigate the change in learners' acquisition of English expressions. As a result, subjects' learning of English expressions showed a significant improvement over time. An open-ended questionnaire was also conducted to ascertain learners' satisfaction level and their perceptions of classes using animated movie, with learners' satisfaction found to be high overall (77.1%). Students identified the reasons for their high satisfaction rate as the following: "fun and a touching story", "beneficial composition of textbooks", "efficient teaching methods", "sympathetic topics", and "appropriate difficulty". When using video media in class, instructors should maximize and leverage the advantages of video media, which are rich both in context and in their linguistic aspects.

• International Journal of Contents
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• v.9 no.4
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• pp.45-51
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• 2013

The purpose of this paper is to analyze educational theories and practices represented in the movie Dangerous Minds. This paper begins by giving the overview of the movie. Then this paper makes an analysis of the pedagogical methods and practices used by the teacher in the movie, which can encourage students to fulfill their academic success and social mobility. The lives of students at risk are transformed through the teacher's beliefs and pedagogical practices based on the constructivism, leading students on a path of selfdiscovery and self-empowerment. What is imperative in the students' lives here is their intrinsic motivation and self-efficacy toward the self and their educational system. By providing constructivist pedagogical paradigms and viewing these media texts within the context of an urban school, this paper intends to introduce educational theories and methods which can create better educational environment for students. In short, this study explores teaching theories and methods represented in the movie based on the constructivist perspectives, which are supposed to fully cultivate the potential of students.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.19-33
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• 2022

With the explosive growth of social media, its abundant text-based data generated by web users has become an important source for data analysis. For example, we often witness online movie reviews from the 'Naver Movie' affecting the general public to decide whether they should watch the movie or not. This study has conducted analysis on the Naver Movie's text-based review data to predict the actual ratings. After examining the distribution of movie ratings, we performed semantics analysis using Korean Natural Language Processing. This research sought to find the best review rating prediction model by comparing machine learning and deep learning models. We also compared various regression and classification models in 2-class and multi-class cases. Lastly we explained the causes of review misclassification related to movie review data characteristics.

• Journal of Information Technology Applications and Management
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• v.26 no.3
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• pp.19-27
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• 2019

In this study, we propose a methodology for predicting the movie audience based on movie information that can be easily acquired before opening and effectively distinguishing qualitative variables. In addition, we constructed a model to estimate the number of movie audiences at the time of data acquisition through the configured variables. Another purpose of this study is to provide a criterion for categorizing success of movies with qualitative characteristics. As an evaluation criterion, we used information gain ratio which is the node selection criterion of C4.5 algorithm. Through the procedure we have selected 416 movie data features. As a result of the multiple linear regression model, the performance of the regression model using the variables selection method based on the information gain ratio was excellent.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.7
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• pp.37-47
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• 2017

The purpose of this study is to investigate how flip learning based interdisciplinary fusion creativity promotion program using movie is effective for university students creativity and fusion talent literacy. To do this, we conducted a total of 15 sessions for a total of 89 students from 44 college students and 45 non - attendance college students who attended the "Creative Fusion Creative Encounters with Film" course at Busan Metropolitan City. The collected data were analyzed by independent sample t-test using SPSS 23.0 program. The results of this study are as follows. First, flip learning based interdisciplinary fusion creativity enhancement program using movie was significant in the order of patience / attachment, humor, self - confidence, imagination, openness, independence, and curiosity in the creativity sub - domain of college students. Second, flip learning - based interdisciplinary convergence creativity enhancement programs using movies were found to have a significant effect in the order of convergence, care, communication, and creativity in the sub - areas of university students' literacy achievement. The findings of the study proved the educational effects of the interdisciplinary creativity promotion program that was based on movie-assisted flipped learning, and this study is expected to suggest some of the right directions for education-based interdisciplinary research and to give some suggestions on that.

• Journal of the Korean School Mathematics Society
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• v.13 no.1
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• pp.125-141
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• 2010

The aim of this paper is to develop a web-based Virtual Learning System for discrete mathematics learning using CAS (Computer Algebra System), The system contains a series of contents that are common between secondary und university curriculum in discrete mathematics such as sets, relations, matrices, graphs etc. We designed and developed web-based virtual learning contents contained in the proposed system based on Mathematia, webMathematica and phpMath taking advantages of rapid computation and visualization. The virtual learning system for discrete math provides movie lectures and 'practice mode' authored with phpMath in order to enhance conceptual understanding of each movie lesson. In particular, matrix learning is facilitated with conceptual diagram that provides interactive quizzes. Once the quiz results are submitted, Bayesian inference network diagnoses strong and weak parts of learning nodes for generating diagnostic reports to facilitate personalized learning. As part of formative evaluation, the overall responses were collected for future revision of the system with 10 university students.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.471-478
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• 2022

In a good class, the elements that make up the class are organically related as a system. Unilateral assessment without sufficient explanation or agreement on assessment criteria, subjective assessment that does not guarantee the reliability of the assessment process and decolonized evaluation separate from the learning process can be a threat to a good class or healthy learning ecosystem. This study analyzed the evaluation through rubric and its effects to solve problems related to educational evaluation. 'Rubrick' is a descriptive evaluation tool that details the criteria for evaluating performance tasks based on class goals and the quality of performance in several stages. The rubric applied for movie literacy evaluation is 'analytical rubric'. It covers literacy to understand movies, movie making literacy and movie utilization literacy. For rubric, learners recognized it as a valid and very useful learning reflection tool.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.1-8
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• 2008

The information system in which users can utilize to control and to get the filtered information efficiently has appeared. Content-based filtering can reflect content information, and it provides recommendation by comparing the feature information about item and the profile of preference. This has the shortcoming of the varying accuracy of prediction depending on teaming method. This paper suggests the discovery of preference through learning the profile for the content-based filtering. This study improves the accuracy of recommendation through learning the profile according to granting the preference of 6 levels to estimated value in order to solve the problem. Finally, to evaluate the performance of the proposed method, this study applies to MovieLens dataset, and it is compared with the performance of previous studies.

• Journal of Information Technology Services
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• v.17 no.1
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• pp.79-89
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• 2018

Sentiment analysis is a technique of text mining that extracts feelings of the person who wrote the sentence like movie review. The preliminary researches of sentiment analysis identify sentiments by using the dictionary which contains negative and positive words collected in advance. As researches on deep learning are actively carried out, sentiment analysis using deep learning model with morpheme or word unit has been done. However, this model has disadvantages in that the word dictionary varies according to the domain and the number of morphemes or words gets relatively larger than that of phonemes. Therefore, the size of the dictionary becomes large and the complexity of the model increases accordingly. We construct a sentiment analysis model using recurrent neural network by dividing input data into phoneme-level which is smaller than morpheme-level. To verify the performance, we use 30,000 movie reviews from the Korean biggest portal, Naver. Morpheme-level sentiment analysis model is also implemented and compared. As a result, the phoneme-level sentiment analysis model is superior to that of the morpheme-level, and in particular, the phoneme-level model using LSTM performs better than that of using GRU model. It is expected that Korean text processing based on a phoneme-level model can be applied to various text mining and language models.