• Title/Summary/Keyword: popularity

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Movie Popularity Classification Based on Support Vector Machine Combined with Social Network Analysis

  • Dorjmaa, Tserendulam;Shin, Taeksoo
    • Journal of Information Technology Services
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    • v.16 no.3
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    • pp.167-183
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    • 2017
  • The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

Popularity versus Influence on SNS (SNS에서 인기도와 영향력의 비교)

  • Lee, Song-ha;Seo, DongBack;Kim, Tae-Sung
    • Information Systems Review
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    • v.17 no.3
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    • pp.183-202
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    • 2015
  • In recent years, various Social Network Service (SNS) is emerging as a new means of communication were enjoying a lot of popularity among consumers. Accordingly, an online word-of-mouth marketing through the SNS is prevalent. At this moment, the majority of companies selects the SNS used as resources of online word-of-mouth marketing on the assumption that the more a SNS is popular (followers or visitors based), the more it has an influence. In addition, the existing studies about the popularity or influence on the SNS were not distinguish them separately. The former researchers used popularity mixed with Influence. Therefore, this study, we have conducted a survey with people in their twentieswho use SNS most to do an empirical analysis of the relationship between popularity and Influence on the SNS. According to the results of this study, it has a weak correlation between popularity and Influence. So, it is necessary to distinguish between popularity and influence.

The Relationship between Children's Popularity and Interpersonal Cognitive Problem-Solving Skill (아동의 또래간의 인기도와 대인문제해결사고와의 관계)

  • Yang, Jin Hee;Choi, Kee Young
    • Korean Journal of Child Studies
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    • v.17 no.1
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    • pp.259-273
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    • 1996
  • The purpose of this study was to investigate the relationship between children's popularity and Interpersonal Cognitive Problem-Solving Skill(ICPS). The subjects were 162 children(70 popular, 76 rejected, and 16 neglected children) chosen from 359 children between the age of 5 -6 and 8-9 years of age. The materials were peer nomination measures developed by Moreno(1934 ) and Interpersonal Cognitive Problem-Solving Skill produced by Park, Chan-Ok from IPCS of Spivack(1976). The data were analyzed by 3-way ANOVA popularity (3) ${\times}$ age (2) ${\times}$ sex (2), t-test, and $Scheff\acute{e}$ test. The results were that (1) children's popularity was significantly different by sex, (2) children's ICPS was significantly different by age for boys, (3) there was no significant difference in ICPS by popularity, and (4) there were significant differences in positive negative solution thought.

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Reationships between Mindreading, Popularity, and Friendship in Preschool Children (아동의 틀린 믿음 및 정서이해 능력과 인기도 및 친구관계의 관련성)

  • Shin, Yoo-Lim
    • Journal of the Korean Home Economics Association
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    • v.43 no.8 s.210
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    • pp.13-23
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    • 2005
  • The purpose of this study was to examine the relationship between mind understanding, popularity, and friendship of preschool children. A total 1444-and 5-year old children participated in this study. The children were assessed on false belief, emotion understanding, language skill, and popularity in peer groups. Their teachers rated the children's friendship qualities. Significant differences in mind understanding based on social status and friendship status were found. Popularity, number of mutual friend, PPVT, and positive interaction between friends were found to be significant predictors of children's mind understanding.

Factors Affecting the Popularity of Video Clip: The Case of Naver TV (영상클립의 인기요인에 대한 실증 연구: 네이버 TV를 중심으로)

  • Yang, Gimun;Chung, Sun Hyung;Lee, Sang Woo
    • The Journal of the Korea Contents Association
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    • v.18 no.6
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    • pp.706-718
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    • 2018
  • This study analyzed Naver TV users' pattern of video clip watching, and analyzed the factors affecting the popularity of Naver TV's video clip. We selected 572 individual video clips that were ranked 50th in Naver TV rankings from September 10th to September 24th in 2017. We classified video clip's characteristics into several factors, including the number of likes, the number of subscriber, genre, video clip's types, and star appearances. We indexed the popularity of video clip, which implies the degree of popularity for each video clip. The results showed that the number of likes for video clips and the number of subscribers for each video clip were positively related to the popularity of video clip. Video clip's genre, video clip's type and star power positively affected the popularity of video clip. The effect of extras genre on the popularity of video clip was the lowest, followed by entertainment, music, and drama genre. but the difference among entertainment, music and drama genre was not statistically significant. Web-only video and non-broadcast video positively affected the popularity of video clip. Finally, the popularity of video clip was higher when stars appeared in the video clip.

An Empirical Study on Forecasting Model of Popularity Rating for Drama Programs (드라마 시청률 예측모델에 대한 실증적 연구)

  • Lee, Won-Jae;Lee, Nam-Yong;Kim, Jong-Bae
    • Journal of Digital Contents Society
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    • v.13 no.3
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    • pp.325-334
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    • 2012
  • Production of drama programs has been granted as a creative work. Thus Systematic approaches to improving quality of drama programs have hardly been tried. This research is for producing a statistical computing model that is capable of forecasting on popularity rating of drama programs produced by KBS, especially forecasting prior to the broadcasting. For the work, we traced various factors affecting on drama popularity ratings, found the relationships among the factors with a regression analysis work, and created the forecasting model on drama popularity ratings. The research result could be applied for finding proper scales of input factors necessary to drama program productions.

Efficient Document Replacement Policy by Web Site Popularity

  • Han, Jun-Tak
    • International Journal of Contents
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    • v.3 no.1
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    • pp.14-18
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    • 2007
  • General replacement policy includes document-based LRU or LFU technique and other various replacement policies are used to replace the documents within cache effectively. But, these replacement policies function only with regard to the time and frequency of document request, not considering the popularity of each web site. In this paper, we present the document replacement policies with regard to the popularity of each web site, which are suitable for modern network environments to enhance the hit-ratio and efficiently manage the contents of cache by effectively replacing documents on intermittent requests by new ones.

Bullying Situations : Gender Differences in Social Status and Social Emotions of Participant Roles (또래 괴롭힘 참여자의 사회적 지위 및 사회적 정서에 관한 연구 : 성별을 중심으로)

  • Sim, Hee-og
    • Korean Journal of Child Studies
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    • v.29 no.3
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    • pp.191-205
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    • 2008
  • This study explored gender differences in social status, acceptance/rejection, perceived popularity, social emotions, avoidance and anxiety by participant roles in bullying situations. Subjects were 215 6th grade children. Instruments were the Participant Roles (Sutton & Smith, 1999), Peer Nomination (Coie & Dodge, 1983 Cillessen & Mayeux, 2004), Social Avoidance and Social Anxiety (Franke & Hymel, 1984) scales. Results showed that more boys than girls were in pro-bullying participant role groups; more girls than boys were in outsider groups. Boy pro-bullies were high in social rejection. Boy defenders were high in popularity and low in social avoidance. Boy outsiders had high social anxiety. Girl victims had low social status, low social acceptance and lowest perceived popularity; they were high in social avoidance and social rejection.

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Strategies for Selecting Initial Item Lists in Collaborative Filtering Recommender Systems

  • Lee, Hong-Joo;Kim, Jong-Woo;Park, Sung-Joo
    • Management Science and Financial Engineering
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    • v.11 no.3
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    • pp.137-153
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    • 2005
  • Collaborative filtering-based recommendation systems make personalized recommendations based on users' ratings on products. Recommender systems must collect sufficient rating information from users to provide relevant recommendations because less user rating information results in poorer performance of recommender systems. To learn about new users, recommendation systems must first present users with an initial item list. In this study, we designed and analyzed seven selection strategies including the popularity, favorite, clustering, genre, and entropy methods. We investigated how these strategies performed using MovieLens, a public dataset. While the favorite and popularity methods tended to produce the highest average score and greatest average number of ratings, respectively, a hybrid of both favorite and popularity methods or a hybrid of demographic, favorite, and popularity methods also performed within acceptable ranges for both rating scores and numbers of ratings.

Video and Computer Game Use and the Sociality of Young Children (유아의 전자게임 이용과 사회성에 관한 연구)

  • 조경자
    • Journal of the Korean Home Economics Association
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    • v.40 no.9
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    • pp.35-46
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    • 2002
  • This study was to investigate whether there are any differences in social competence by the frequency of young children's video and computer game use. Social development was categorized as peer popularity and social competence. The subjects were 215 children(118 boys, 97 girls) aged 4-6 years(M= 63.6 months, SD=6.8) from 3 kindergartens in Chung-Cheong Nam Do. The frequency of children's video and computer game use was reported by their parents. Peer popularity was rated by their classmates and social competence by their teachers with Kohn Social Competence Scale(KSCS). No significant relationship was found between game use and peer popularity. The children who played video and computer games once or twice a week got the highest score on the‘social interest and participation’But social cooperation dimension was not related with the frequency of video and computer game use but with the sex of children.