• Journal of People, Plants, and Environment
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• v.24 no.2
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• pp.209-218
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• 2021

Background and objective: Instagram, an image-based social media, is being used as an important outlet for the communication and place marketing of public spaces. The purpose of this paper was to analyze how types of place-based content affect user reactions (Likes and Comments) on Instagram in order to provide basic data on the operation and utilization of social media by public places such as botanical gardens and arboretums. Methods: A total of 850 posts uploaded to the Instagram account of Kew Gardens from November 6, 2014 to July 3, 2020 were classified using 14 subject codes. Multiple regression analysis was performed to evaluate the user's reaction between the dependent variables ("Likes", "Comments") and the independent variables (14 subject codes). Results: The findings showed that user reactions appear to differ depending on the typology of the content, and "Likes" and "Comments" were presented in independent behavioral reactions. In particular, "close-ups of plants (botanic, macro)," "plant colony (botanic, wide)," "place-specific landscape (building, landscape)," "anniversary" and "information" showed positive impacts on both "Likes" and "Comments"which could lead to electronic word-of-mouth and content sharing. Conclusion: Based on these findings, it can be argued that the typology of a botanical garden's content can be used to determine factors that affect the immediate reactions and enhance engagement with users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3023-3036
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• 2019

This study investigated the television (TV) content viewers' behavior influenced by online communication at the choice of new TV series on a terrestrial streaming platform. For exploring the impact of the anchoring effect on the TV content consumption, this study analyzed the correlation between the first episode's TV ratings and the data of online comments or reactions. These data were potential audiences' communication, which were generated on the online article three weeks before the first broadcasting began. To avoid the crucial influence by external factors, such as season and social issue, the test was done with eight (8) TV series which have same genre (drama), similar core audience targeting (20-49's women), similar broadcasting period (Jun-Oct 2016), same scheduling (10.00 to 11.00 pm, weekdays) and aired on terrestrial TV platforms. This research found that not only the amount of comments and reactions, but also the attitude about the comments created before broadcasting, positively influence the audiences' decision-making behavior for new TV content choices. This investigation contributes to the literature on media economics and management by exploring the media content users' consuming behavior with behavioral economics perspectives (anchoring effect) and making a first step for finding a new effect on the media content consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2491-2508
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• 2019

This research investigates the media consumers' behavior with behavioral economics perspective, especially regarding TV content viewers' behavior; how do online communications influence TV viewers' decision when choosing a new TV content among options. We focus on quantity and attribute of comments or reactions on the online news articles. We analyze that online communications data, which were generated before the first broadcast, affect the TV content consumers' choice for a new TV series. Here we identify a predicted utility, experienced utility and distinction bias in TV media consumption to find the effectiveness of the first viewing choice on whole TV series' episodes. To avoid the crucial influence by exogenous factors, such as season and social issue, the test was done with specific conditions. This research found that the total number of reactions to the comments by itself positively affects the audiences' decision-making behavior for a new TV content choice. This influence was regardless of favor/ non-flavor reactions. This study contributes to the literature on media economics and management by exploring the media content users' consuming behavior and making a first step for finding an important influencer on the media content consumption.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.189-198
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• 2019

This study aims to make meaning of the reactions of the Korean people through the text mining of comments on videos of the December 2018 MMA performance of intro on YouTube. For this, comments on 15 YouTube videos were collected over the past 10 months. With the collected data, a total of 5,135 comments were analyzed through crawling using the Python and BeautifulSoup programs, data was refined over a total of 3 sessions, and a final total of 5,080 comments were used as analysis material. A mining technique was used for data analysis and the process of refinement, analysis, and visualization was achieved using the Textom program. Research results showed that keyword analysis showed the keywords of 'performance', 'Korea', 'video', 'top', 'cool', 'dance', 'idol', 'legend', 'love', and 'gratitude' in that order and keywords such as 'patriotism' and 'Olympics' also appeared frequently. N-gram analysis showed that comments with contexts such as 'a top performance that will remain a legend among Korean idol performances', and 'an idol performance that displayed the traditional culture of Korea' were in higher ranks. Based on such keyword analysis results, topic modeling was applied and 5 top keywords were extracted from a total of 5 topics. Analysis results of topic contents and distribution showed that topics in the comments of this performance's videos largely consisted of the 3 reactions of 'high praise regarding the stage performance', 'affection towards the fusion and artistic sublimation of Korean traditional dance', and 'gratitude towards the uploading of cool dance videos'

• The Journal of Information Systems
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• v.32 no.4
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• pp.29-50
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• 2023

Purpose The impact of online reviews is widely acknowledged, with extensive research focused on text-based reviews. However, there's a lack of research regarding reviews in video format. To address this gap, this study aims to explore the connection between company-sponsored product review videos and the extent of directive speech within them. This article analyzed viewer sentiments expressed in video comments based on the level of directive speech used by the presenter. Design/methodology/approach This study involved analyzing speech acts in review videos based on sponsorship and examining consumer reactions through sentiment analysis of comments. We used Speech Act theory to perform the analysis. Findings YouTubers who receive company sponsorship for review videos tend to employ more directive speech. Furthermore, this increased use of directive speech is associated with a higher occurrence of negative consumer comments. This study's outcomes are valuable for the realm of user-generated content and natural language processing, offering practical insights for YouTube marketing strategies.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.119-133
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• 2020

Recently, as famous YouTubers produce and broadcast videos that receive sponsorship and advertising such as indirect advertising (PPL), a so-called 'back advertising' controversy continues, and not only famous YouTubers but also entertainers are caught up in the issue. It is causing confusion among the public in Korea. This study attempts to find out the public's reaction before and after the controversy of 'back advertising' by YouTubers through comment analysis. Specifically, among text analysis using R programs, we intend to analyze the issue through various methods such as word cloud, qgraph analysis, LDA, and word2vec analysis, a deep learning technique. The target of the analysis was to analyze the channels of three YouTubers who belonged to the controversy of the 'back advertising' YouTuber and uploaded the 'Apology video'. The 5 most recent videos of Muk-bang YouTuber Moon Bok-hee, who has a similar content disposition to SussTV's Han Hye-yeon stylist, which was controversial, and Yang Pang, a YouTuber who showed various contents (August 09, 2020) Criterion and her first 5 videos uploaded were reviewed. As a result of the study, most of the comments that showed positive reactions before the controversy, but after the controversy, it was found that negative reactions accounted for most of the comments. Therefore, this study examines the degree of change of the public about influencers through comments after the controversy over 'back advertising' through various analysis using R program. This research also devises various measures to prevent the occurrence of back advertising of influencers in the future.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.28-36
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• 2022

This study analyzed 284 K-pop song and dance cover short-form videos recreated by Chinese influencers uploaded on TikTok, to explore which reform factors of image similarity, language similarity, the extent of audience participation leading, the extent of lyrics or subtitles translated into Chinese, PPL disclosure, the length of video and the reputation of influencer affected Chinese TikTok audiences' reactions - number of "Likes," "Comments" and "Shares." The results showed that only the "reputation of influencer" was significantly affected the number of "Likes" which estimated as a relatively passive response, but the other factors affected the number of "Comments" and "Shares" significantly which estimated as more active responses. The more an influencer is perceived as not similar to the singer in terms of image the more comments were posted. And the videos expressed in Korean archived more comments and shares than those lyrics or subtitles translated into Chinese. This study is meaningful in that it confirmed the necessity of influencers in the globe diffusion of K-pop, by specifically analyzing the audience's reactions according to the characteristics of UCCs created by local influencers using short-form video platforms.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.107-115
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• 2023

This study analyzes the content of YouTube Vlog videos created by patients of Coronavirus disease 2019 ("COVID-19") in South Korea and viewer comments on those videos. As this new infectious disease started to sweep the world in late 2019 and early 2020, the public started facing fear and uncertainty stemming from the lack of sufficient and accurate information about the virus. At the same time, as COVID-19 patients in South Korea were treated in isolation to prevent the spread of the virus, the patients themselves were experiencing anxiety and exclusion from the society. During this period, there was an increase in YouTube Vlog videos created by the patients in which they shared their experiences going through the treatment and recovery processes. To understand how these YouTube Vlog videos were being used by the patients to connect with the society and seek support in a state of isolation and anxiety, this study conducted a qualitative multi-case analysis of three sample YouTube Vlog video channels to analyze their content, as well as a lexicon-based sentiment analysis of viewer comments to understand the experiences and reactions of viewers. The patients' YouTube Vlog videos showed that they shared similar stages of progress, despite each emphasizing a different main theme. Overall, the tone of the viewer comments became increasingly positive over time, although with some variance among different patient cases and stages. The results confirmed that Vlogs of patients played a significant role in reducing the uncertainty around COVID-19 and strengthening social support for the patients. The findings of this study can improve an understanding of the psychological and behavioral aspects of patient experience in isolated treatment and the impact of shared communication among members of society in times of crisis.

• Journal of Information Technology Services
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• v.23 no.3
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• pp.103-118
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• 2024

Due to the advancement of virtual reality technology, virtual idols are widely used in industrial and cultural content industries. However, it is difficult to utilize virtual idols' social perceptions because they are not properly understood. Therefore, this paper collected and analyzed YouTube comments to identify differences about social perception through comparative analysis between virtual idols and general idols. The dataset was constructed by crawling comments from music videos with more than 10 million views of virtual idols and more than 10,000 comments. Keyword frequency and TF-IDF values were derived from the collected dataset, and the connection centrality CONCOR cluster was analyzed with a semantic network using the UCINET program. As a result of the analysis, it was found that virtual idols frequently used keywords such as "person," "quality," "character," "reality," "animation," while reactions and perceptions were derived from general idols. Based on the results of this analysis, it was found that while general idols are mainly evaluated with their appearance and cultural factors, social perceptions of virtual idols' values are mixed with evaluations of cultural factors such as "song," "voice," and "choreography," focusing on technical factors such as "people," "quality," "character," and "animation." However, keywords such as "song," "voice," "choreography," and "music" are included in the top 30 like regular idols and appear in the same cluster, suggesting that virtual idols are gradually shifting away from minority tastes to mainstream culture. This study aims to provide academic and practical implications for the future expansion of the industry and cultural content industry of virtual idols by grasping the social perception of virtual idols.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.25-31
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• 2018

Online news has replaced the traditional newspaper and has brought about a profound transformation in the way we access and share information. News websites have had the ability for users to post comments for quite some time, and some have also begun to crowdsource reactions to news articles. The field of sentiment analysis seeks to computationally model the emotions and reactions experienced when presented with text. In this work, we analyze more than 100,000 news articles over ten categories with five user-generated emotional annotations to determine whether or not these reactions have a mathematical correlation to the news body text and propose a simple sentiment analysis algorithm that requires minimal preprocessing and no machine learning. We show that it is effective even for a morphologically complex language like Korean.