• Journal of Convergence for Information Technology
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• 제11권9호
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• pp.214-220
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• 2021

With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.

• Journal of Information Science Theory and Practice
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• 제7권2호
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• pp.40-53
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• 2019

Although fake news has been present in human history at any time, nowadays, with social media, deceptive information has a stronger effect on society than before. This article answers two research questions, namely (1) Is the dissemination of fake news supported by machines through the automatic construction of filter bubbles, and (2) Are echo chambers of fake news manmade, and if yes, what are the information behavior patterns of those individuals reacting to fake news? We discuss the role of filter bubbles by analyzing social media's ranking and results' presentation algorithms. To understand the roles of individuals in the process of making and cultivating echo chambers, we empirically study the effects of fake news on the information behavior of the audience, while working with a case study, applying quantitative and qualitative content analysis of online comments and replies (on a blog and on Reddit). Indeed, we found hints on filter bubbles; however, they are fed by the users' information behavior and only amplify users' behavioral patterns. Reading fake news and eventually drafting a comment or a reply may be the result of users' selective exposure to information leading to a confirmation bias; i.e. users prefer news (including fake news) fitting their pre-existing opinions. However, it is not possible to explain all information behavior patterns following fake news with the theory of selective exposure, but with a variety of further individual cognitive structures, such as non-argumentative or off-topic behavior, denial, moral outrage, meta-comments, insults, satire, and creation of a new rumor.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제25권1호
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• pp.1-7
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• 2021

Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.

• Journal of the Korea Convergence Society
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• 제12권11호
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• pp.229-234
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• 2021

This study identified the characteristics of video contents related to waste cycle in Korean social media. The contents of broadcasting companies were the most popular among production entities, and mainly current affairs contents and educational contents were popular. Among the solutions to recycle wastes, 'Improvement of systems and policies' was predominantly covered in the video as solutions to the waste circulation problems. 'Broadcasting companies', 'local governments', 'non-profit private organizations' and 'central administrative agencies' actively used the social media to deliver solutions and engage consumers. However, very few contents were produced by companies that are socially responsible for waste. The results of this study show the importance of communication-oriented, public-friendly content development in the process of video production related to waste cycle. These are expected to be useful guidelines for decision-making supporting the development and improvement of related systems and policies.

• Korean Journal of Culture and Social Issue
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• 제27권2호
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• pp.191-216
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• 2021

How an individual construes one's future influences everyday decisions. For example, savings and impulsive purchasing, which is highly familiar with our life, are related to future time perception. Drawing on the idea of future self-continuity, the perceived connectedness between the current and future self, this study demonstrated whether media images with various age ranges influence a sense of connectedness with one's future self as well as impatience. Furthermore, the study measured whether these relationships were moderated by the positivity of older adults and an individual's dispositional optimism in general. Results showed that watching various images of people with a wide range of age (from the 20s to 90s) in social media increased young adults' (the 20s) self-continuity and decreased their intention of impatient consumption. This effect was also moderated by the degree to which the participants perceive aging positively.

• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.53-62
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• 2022

Disposition Effect (DE) is one of the many investment biases, wherein the investors sell the profitable stocks rather quickly and they tend to hold on the loss making stocks. Various factors related to the DE are the character of investors applying risk management which is also influenced by the social media, Salient Shock (COVID-19), and in the specific case of Indonesia, the phenomenon of rumor stocks wherein the price can rise as much as up to 8500%. The study aims to provide empirical evidence regarding the DE with specific explanatory factors, namely investor behavior and rumors. Data was obtained through a questionnaire sent to 248 Indonesian Stock Exchange Investors (IDX) during the period October-November 2021 by using Ordinary Least Square (OLS) method. The results show: Generation Z, women, and investors with a low education has a greater DE, risk-takers tend to have lower DE, and professionals have negative DE. Implementation of risk management will reduce DE. Social Media and the COVID-19 situation positively affect DE. Especially on stock rumors, there is evidence that investors who own rumor stocks will have a low DE. The results indicate the need for: (i) risk management, especially for Z Generation, women and low education Investors, (ii) to provide positive information so that information on social media can be responded to positively.

• Journal of Information Technology Services
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• 제22권3호
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• pp.101-118
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• 2023

The 'MZ generation' is accustomed to expressing their thoughts and opinions online. As a result, the role of social media in understanding the opinions and public sentiment of the MZ generation has become increasingly important. In particular, the role of social media in understanding the opinions of young people in political contexts such as policies and elections is becoming more significant. Traditionally, in such political situations, various institutions conduct opinion surveys to grasp the opinions of the people. However, existing opinion surveys have many errors and limitations in understanding the specific opinions of the entire population since they are conducted on arbitrary individuals through survey techniques. Online communities are representative social media that share the opinions of the public on specific issues such as politics, economics, and culture. Therefore, online communities are widely used as a means to supplement the limitations of traditional opinion polls. In particular, the MZ generation is familiar with online platforms, and their political support has significant influence on election results and policy decisions. With this regard, this study analyzed the relationship between the sentiment reflected in online community text data by age group on major candidates and public opinion survey support rates during the Korean presidential election for those in their 20s. The analysis showed that negative sentiments reflected in online communities by the MZ generation have a negative correlation with public opinion survey support rates. This study contributes to theory and practice by revealing a significant association between social media and public opinion polls.

• The korean journal of orthodontics
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• 제53권5호
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• pp.328-335
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• 2023

Objective: The aim of this study was to determine whether an association between study quality, other study characteristics, and Altmetric Attention Scores (AASs) existed in orthodontic studies. Methods: The Scopus database was searched to identify orthodontic studies published between January 1, 2017, and December 31, 2019. Articles that satisfied the eligibility criteria were included in this study. Study characteristics, including study quality were extracted and entered into a pre-pilot data collection sheet. Descriptive statistics were calculated. On an exploratory basis, random forest and gradient boosting machine learning algorithms were used to examine the influence of article characteristics on AAS. Results: In total, 586 studies with an AAS were analyzed. Overall, the mean AAS of the samples was 5. Twitter was the most popular social media platform for publicizing studies, accounting for 53.7%. In terms of study quality, only 19.1% of the studies were rated as having a high level of quality, with 41.8% of the studies deemed moderate quality. The type of social media platform, number of citations, impact factor, and study type were among the most influential characteristics of AAS in both models. In contrast, study quality was one of the least influential characteristics on the AAS. Conclusions: Social media platforms contributed the most to the AAS for orthodontic studies, whereas study quality had little impact on the AAS.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• The Research Journal of the Costume Culture
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• 제32권2호
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• pp.215-231
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• 2024

The changing media landscape has diversified how and what is discussed about fashion. This study aims to examine expert discussions about fashion shows on social media from the perspective of fashion criticism. To achieve this goal objectively, a text mining program, Leximancer, was used. In total, 58 videos were collected from the panel discussion section of Showstudio from S/S 21 to S/S 24, and the results of text mining on 24,080 collected texts after refinement are detailed here. First, the researchers examined the frequency of keywords by season. This revealed that in 2021-2022, digital transformation, diversity, and fashion films are now commonly used to promote fashion collections, often replacing traditional catwalk shows. From 2023, sustainability and virtuality appeared more frequently, and fashion brands focused on storytelling to communicate seasonal concepts. In S/S 2024, the rise of luxury brand keywords and an increased focus on consumption has been evident. This suggests that it is influenced by social and cultural phenomena. Second, the overall keywords were analyzed and categorized into five concepts: formal descriptions and explanations of the collection's outfits, sociocultural evaluations of fashion shows and designers, assessments of the commerciality and sustainability of the current fashion industry, interpretations of fashion presentations, and discussions of the role of fashion shows in the future. The significance of this study lies in its identification of the specificity of contemporary fashion criticism and its objective approach to critical research.