• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.2 no.2
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• pp.147-154
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• 1969

The larvae of the ark shell Anadare broughtoni(Schrenck) were grown at room temporature (approximately $20.4^{\circ}C$), and fed laboratory-cultured Cyclotella nana. The egg of the ark shell produced in the laboratory measured about $54.9\mu$ in diameter. The embryos gradually developed into larvae up to $110.8\mu$ shell length, $83.9\mu$ shell height and with shell breadth of $58.2\mu$ even in the absence of the algal food. Beyond this sire, however, the growth of the larvae was considerably retarded. The larvae showed better growth rate when they were fed the algal food two days after spawning, i. e., early straight-hinge stage. Daily rate of food consumption varies according to the larval sizes. But the rate increases considerably when the larvae begin to form umbos. In general the rate Is indicated by the following formula: $Y=0.0025161\;X^{2.76459}$. The growth experiments of the larvae indicate that the efficiency of food conversion was higher when fed centrifuged food. Regarding to the difference in the slopes of growth curve, centrifuged food showed better growth rate as compared to those grown with the non-centrifuged food. The smaller the larval size, the greater will be the difference in growth. The larvae began settling when they reathed 261.7 to $289.6\;{\mu}$ in shell length, 199.2 to $221.7\mu$ in shell height and 147.6 to $170.8\mu$ in shell breadth. The time which elapsed from spawning to the larval settlement was about 28 days. The mean growth of the larvae is indicated with regression line and exponential curve equations as follows. Regression line shell length. 94.3 to $133.9\mu$ : Y==85.22857+3.35000X 141.6 to $269.3\mu$: Y=10.83036X-36.05357 296.8 to $373.2\mu$ : Y=19.10000X-279.30000 shell height: 72.7 to $89.7\mu$ : Y=67.11429+2.15714X 108.4 to $206.4\mu$ : Y=8.31607X-27.45357 228.6 to $282.1\mu$: Y=173.46700+13.37500X shell breadth: 45.3 to $77.8\mu$ : Y=38.08510X+2.73570X 87.4 to $157.7\mu$: Y=5.77320X-5.99640 175.4 to $214.0\mu$: Y=19.65000X-114.13300 Exponential curve shell length. 94.3 to $373.2\mu$: Y=72.45 $e^{0.04697x}$ shell height: 72.7 to $282.1\mu$: Y=54,96 $e^{0.04720x}$ shell breadth: 45.3 to $214.0\mu$ : Y=39.82 $e^{0.04927x}$ The relationships between the shell length and shell height and between the shell length and shell breadth are indicated as follows- shell height: 72.7 to $98.7\mu$ : Y=12.87780+0.63817X 108.4 to $206.4\mu$ : Y=0.90220+0.76456X 228.6 to $282.1\mu$ : Y=25.02630+0.69156X shell breadth: 45.3 to $77.8\mu$:Y=0.81373Xx-31.18914 87.4 to $157.7\mu$ : Y=13.37549+0.53230X 175.4 to $214.0\mu$: Y=30.24328+0.49545X