• Journal of Digital Convergence
• /
• v.16 no.3
• /
• pp.145-156
• /
• 2018

Unlike the past, when distributors distributed games through retail stores, they are now selling digital content, which is based on online distribution channels. This study analyzes the effects of eWOM (electronic Word of Mouth) on sales volume of game sold on Steam, an online digital content distribution channel. Recently, data mining techniques based on Big Data have been studied. In this study, emotion index of eWOM is derived by emotional analysis which is a text mining technique that can analyze the emotion of each review among factors of eWOM. Emotional analysis utilizes Naive Bayes and SVM classifier and calculates the emotion index through the SVM classifier with high accuracy. Regression analysis is performed on the dependent variable, sales variation, using the emotion index, the number of reviews of each game, the size of eWOM, and the user score of each game, which is a rating of eWOM. Regression analysis revealed that the size of the independent variable eWOM and the emotion index of the eWOM were influential on the dependent variable, sales variation. This study suggests the factors of eWOM that affect the sales volume when Korean game companies enter overseas markets based on steam.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.197-218
• /
• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

• Journal of Information Technology Applications and Management
• /
• v.13 no.3
• /
• pp.181-200
• /
• 2006

The purpose of this study is to examine factors influencing online product transformation focusing on benefits of online shopping and word of mouth. Generally, it has been known that buying search goods is more proper than experience goods in the online. However benefits of online shopping and word of mouth make product transformation from experience goods to search goods and the product transformation promote the purchase of experience goods online. We developed a conceptual model of online product transformation including benefits of online shopping(e.g. good price and convenience), online word of mouth (e.g. bulletin board and consumer reviews), and consumer characteristics (e.g. innovativeness and Internet usage). Also, we suggest several research propositions on online product transformation. The implications for marketing strategies of experience goods and furher research direction are suggested.

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

• The Korean Journal of Food And Nutrition
• /
• v.24 no.2
• /
• pp.217-225
• /
• 2011

The current research identified the impacts of WOM(Word-of-Mouth) regarding dining experience and the factors which were likely to influence them. Specifically, this study is examined from the perspective of WOM recipient's in on-line settings. For the purpose of this research, online survey was used and a total 203 online questionnaires of respondents who had experienced restaurant reviews and recommendations via internet last 6 month were analyzed. Overall, the results indicated that in aspects of WOM recipients, the impacts of WOM were 'visit intention', 're-WOM intention' and 'source credibility' affected 'WOM acceptance' in this process. Additionally, 'online homophily' and 'message vividness' had a positive effects(p<0.001) on builiding source credibility. By clarifying the process between on-line WOM of restaurant consumers and their actual visit, this study intend to provide basis which can be used for restaurant industry's effective marketing activity.

• Journal of Fashion Business
• /
• v.25 no.5
• /
• pp.149-162
• /
• 2021

Nowadays, the cosmetic and fashion industries are paying attention to influencer marketing on Instagram. In this study, we determined whether electronic word of mouth (e-WOM) communications were affected by the following parameters: the influencer's information source, message sidedness, and consumer's regulatory focus. The experimental design of this study is a three-way mixed ANOVA, which comprises of 2 (influencer information source: expert vs general consumer) × 2 (message sidedness: two-sided message vs one-sided message) × 2 (consumer regulatory focus: promotion focus vs prevention focus) structure. The data for this research study was obtained by distributing a questionnaire to 410 subjects. The participants were aged between 20 and 39 years and lived in Seoul and Gyeonggi areas. In total, the data of 396 subjects was analyzed with the help of SPSS 25.0 statistical program: frequency analysis, reliability analysis, t-test, three-way ANOVA, and simple main effect analysis were performed. The analysis results were as follows: First, influencer information sources and consumer regulatory focus exhibited a significant interaction with consumers' e-WOM intentions. Second, message sidedness and consumer's regulatory focus exhibited a significant interaction with e-WOM intentions. Third, influencer information source and message sidedness exhibited a significant interaction with consumers' e-WOM intentions. Based on these findings, the type of influencer's information source and the consumer's regulatory focus was taken into consideration while marketing cosmetics on Instagram. Moreover, influencer marketing strategies must be used to evaluate message sidedness. This would help us gauge the consumer's attitude towards advertisements.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.75-94
• /
• 2011

In this paper, we explore the information diffusion mechanism under social network environments by investigating the effect of message characteristics on the volume and speed of retweeting in Twitter, a popular online social media service. To this end, we select eight main keywords (i.e., '무상급식', '반값등록금', '나가수', '평창', '김연아', '박태환', '아이폰', '갤럭시') that have been popular on online social media in recent days. Each keyword represents various social aspects of Korea that recently grab people's attention such as political issues, entertainment, sports celebrities, and the latest digital products, and eventually holds distinctive message characteristics. Analyzing the frequency and velocity of retweeting for each keyword, we find that more than half of the sample messages posted on Twitter contain personal opinions for the certain keyword, but we also find that the tweets which include objective messages with hyperlink are the fastest ones when being retweeted by other followers. In overall, when being retweeted, the group of messages related to the certain keyword present distinctive diffusion patterns and speed according to message characteristics. From academic perspective, the findings in the study broaden our theoretical knowledge of information diffusion mechanism over online social media. For practitioners, the results also provide managerial implications regarding how to strategically utilize online social media for marketing communications with customers.

• The Journal of the Korea Contents Association
• /
• v.21 no.11
• /
• pp.257-267
• /
• 2021

This study warns of the dangers of pre-marketing that is too preoccupied with raising market expectations before release at the film market level, and provides practical implications that the lower the level of mismatch of market expectations, the more ideal performance can be achieved. The level of expectation before release and satisfaction after release were measured by each movie rating, and the difference was calculated as the inconsistency of expectations. In raising expectations before the release, the expert rating among the star power, director power, expert rating, and number of screens has a significant influence. It was confirmed that the level of expectation before the release had a positive effect on the rating after the release, but had a negative effect on the level of discordance. In addition, the hypothesis that the higher the expectation level before the release, the greater the inconsistency, and the hypothesis that the higher the expectation inconsistency has a negative effect on the box office level is supported. This provides various implications for marketing carried out before or after the release of a movie to film-related practitioners for products with low involvement or emotional content such as movies.

• Journal of Digital Convergence
• /
• v.6 no.4
• /
• pp.91-104
• /
• 2008

This study notes the growing importance of online community as a means of building customer relationships. The author aims to identify how to communicate in an online community on preannounced new products, and test social influence that influence word-of-mouth of consumers, and confirm moderate effect of market maven between social influence and word-of-mouth activity in on-line community. The main findings are that social influence such as internalization and conformity positively influence word-of-mouth communication on online community. And moderate effect of market maven confirm between social influence(internalization and confirmity) and word-of-mouth activity.

• International Commerce and Information Review
• /
• v.10 no.4
• /
• pp.63-79
• /
• 2008

Present paper aims to examine the effect relation among component factors of WOM effects in on-line. Specially, to examine the comparative study on market maven and early adopter. For that purpose, we categorize WOM effect into two subcategories; knowledge improvement, Image improvement, purchase intention. And as the of study, chose student a college. Through these methods, we were able to obtain participation of 96 people from student a college. Using 68 responses(19 responses removed). we derived statistics by means of Win SPSS Version 12.0 statistics program package. The result can be summarized as follow; First, market maven has stronger WOM Effects in On-line on consumer's knowledge improvement, and Image improvement, purchase intention than early adopter. Second, the market maven has stronger effect on early adopter. Finally, we discuss the results of analysis and suggest research limitation and future and future study.