• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.71-89
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• 2016

Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

• Journal of Distribution Science
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• v.13 no.10
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• pp.109-114
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• 2015

Purpose - The movie market has the characteristics of being a perfectly competitive market as well as a pure monopolistic market at the same time. This is because there are competitors in the industry but prices, although not fixed, have not changed a lot. Price competition may not have spread, but the competition is focused on artistic value, and the degree of box office success is most important. The artistic value is determined in the course of the production process. However, the degree of box office success is dependent upon the marketing manager. The marketing strategy represents the difference in the standard or quality of the movie. Inherently, the marketing manager adopts the entertainment strategy based on the quality of the foundation of the completed movie. At this time, the marketing manager knows the pertinent information (high quality/low quality) regarding the movie. This research study tries to reveal what should be the reasonable movie marketing expense, dependent on the quality of the movie. Research design, data, and methodology - Using a game scenario with different market players, the goal of the research analysis is to find out the following. First, the marketing expense is determined to maximize the profits after film production. Second, after the production costs are already committed, the manufacturer gets to choose the marketing level. At this time, there will be a profit maximization point, considering the competition. The premise of the research is as follows: if it is a good movie of quality, positive word of mouth increasing the audience continuously slows down the speed of the demand curve. If the movie quality is bad, the negative word of mouth decreasing the audience gradually hastens the speed of the demand curve. On the marketing side, when the manufacturer invests heavily in the marketing expense of the movie, consumer expectations increase to drive up the audience numbers. On the other hand, it is difficult to improve the profits excessively. When the manufacturer invests in marketing a little bit, the marketing expense is only relatively committed, therefore a lot of demand cannot be gained. Results - If a fixed market share is in a competitive situation, a low quality manufacturer expends relatively more marketing expense. If the situation assumes two manufacturers spend the same for the cost of production, the high quality manufacturer takes more profit. If the manufacturer expends less marketing budget to save costs, the optimum profit cannot be achieved since the other party (opponent) grabs the initial market share. Conclusions - In conclusion, investment is essential for market share to increase. We must refrain from a zero-sum game and have models where the game participants pursue the creative profits together. In the current film industry, there is the dominating logic of winner and loser but we have to create a film industry environment where the participants can be altogether satisfied and live together.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.263-270
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• 2014

This paper suggests a method for predicting a box-office success of the film. Lately, as the growth of the film industry, a variety of studies for the prediction of market demand is being performed. The product life cycle of film is relatively short cultural goods. Therefore, in order to produce stable profits, marketing costs before opening as well as the number of screen after opening need a plan. To fulfill this plan, the demand for the product and the calculation of economic profit scale should be preceded. The cases of existing researches, as a variable for predicting, primarily use the factors of competition of the market or the properties of the film. However, the proportion of the potential audiences who purchase the goods is relatively insufficient. Therefore, in this paper, in order to consider people's perception of a movie, Twitter was utilized as one of the survey samples. The existing variables and the information extracted from Twitter are defined as off-line and on-line element, and applied those two elements in machine learning by combining. Through the experiment, the proposed predictive techniques are validated, and the results of the experiment predicted the chance of successful film with about 95% of accuracy.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1259-1269
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• 2015

Recently, big data is positioning as a keyword in the academic circles. And usefulness of big data is carried into government, a local public body and enterprise as well as academic circles. Also they are endeavoring to obtain useful information in big data. This research mainly deals with analyses of box office success or failure of films using text mining. For data, it used a portal site 'D' and film review data, grade point average and the number of screens gained from the Korean Film Commission. The purpose of this paper is to propose a model to predict whether a film is success or not using these data. As a result of analysis, the correct classification rate by the prediction model method proposed in this paper is obtained 95.74%.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.1-14
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• 2021

Recently, crowdfunding platforms have received attention as one of the content investment platforms for the public. This research attempts to explore the influencing factors on the success of movie euqity crowdfunding project. We use 'number of texts', 'number of images', 'star influence power', 'IP-based movie project', 'movie production stage', 'box office prediction', 'investment capital ratio', 'amount of surplus available investment', 'profit calculation method' and 'minimum investment amount' as independent variables. And we examined how these factors affects the achievement rate of movie crowdfunding. As a result of multiple regression analysis, 'movie production stage', 'investment capital ratio', 'amount of surplus available investment' and 'profit calculation method' have a significant effect on the crowdfunding achievement rate. In addition, the results of this research can be used for reference when planning film crowdfunding projects.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.227-239
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• 2022

This study conducted an exploratory empirical analysis on the factors affecting the performance of digital classical music based on signaling theory. For this purpose, using the classical weekly chart provided by the music platform Genie, 297 digital music sources that entered the top 100 chart from March 2020 to October 2020 (35 weeks). In this study, as signals that can influence consumers' choice to listen to classical nusic, we set an the artist's award history, artist's broadcast content linkage, taking the top spot in the first classical music chart entry, producing companies' competency, and the popularity of classical music repertoire. The effect of these signals on the chart success of digital classical music was verified subsequently. As a result of the verification, it was found that the artist's broadcast content linkage, taking the top spot in the first classical music chart entry, and the popularity of the classical music repertoire indeed had a positive effect on the chart success of a classical music. On the other hand, the artist's award history and the producing companies' competence did not significantly affect the chart success of digital classical music. This study is the first empirical study on the success factors of digital classical music performed from a business perspective, and is expected to contribute to subsequent studies related to classical music.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.162-170
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• 2011

Through this thesis, I intended to analyze Hollywood animation through that achieved in box office by directing viewpoint. of Chris Sanders and Dean Deblois not only shows standard narrative structure of adventure, comedy, fantasy, but also express message of story and thorough visual. Analysis of directing classify contents and form. In contents, constitution of narrative and set up of character, irony of plot, characterization and popularity are embossed. In form, lighting and special effect, design and layout, 3D technology and stereoscopic camera technique based on the capital strength are outstanding. The high evaluation for film is possessed of box offic, remained within value and popularity, and delivered metaphysical theme without repulsion. The director's direction make success even if the pre-production manage by huge system approach.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.417-425
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• 2017

The goal of this study is analysing a box office success of The Handmaiden in terms of modified space-time and character. The movie which has original novel induces desire of watching by decreasing property of experience good of movie based narrative of novel. Contrary to novel that is set in Victorian age, the movie changed contents that make a character who realizes masculine of colonialism and women oppressed by man escape through transcending class by adopting period of Japanese occupation. It hereby decreases negative effect by substituting growth and solidarity of women for the element of homosexuality. Also the gender discussion about crimes against female when the movie was running increases factor of sympathy of characters and accord with subject of the movie. Beside that, The reasons of success are detector, star system of actor, effective public marketing of movie trailer and selection of movie won the award for best picture at a film festival.. Movie through adapting novel enhances ability of various creation and blow up appreciation of spectator. The differentiation of adapted hit movie is that the altered content is creative, has subject that corresponding with universal awareness transcending space-time and expresses property of media effectively.

• Cartoon and Animation Studies
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• s.30
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• pp.59-86
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• 2013

'Spectacles' and 'factuality' provided by computer technology are strengths of CG animation to still lure the audience and after commercial success of a number of theatrical CG animations whose typical producing companies are PIXAR and DreamWorks, were produced to be commercially successful and they win massive popularity even now. In Korea as well, several works tried to achieve a box office success including , , etc. but the result was truly miserable. In the past, this failure was often attributed to a lack of 'technical expertise', but it became clear that in the process of continuous trial and error, 'narrative' and 'images of imagination' which are bases and characteristics of animation are key elements of commercial success. Actually, statistics indicate that narrative is what is considered to be the most important by the audience when they select animation and its importance is so absolute that they say the most significant thing in animation is 'story.' In particular, it can be said that 'characters', 'situations', and 'ideas' play a key role in them which become elements of the story. This paper studied with what characteristics each animation aroused pleasure and fun focused on characters, situations and images in relation to , , and which are American theatrical CG animation films which succeeded in gaining popularity home and abroad. We hope that analysis in this paper will be helpful even just a little bit as a reference material, which allows domestic writers and producers to develop familiar and characteristic works based on imagination and creativity expressing each work's unique personality and characteristics.