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Influence of Social Presence on Consumer Purchase Decision at a Retail Store -Shopping Companions, Other Consumers, and Sales Associates- (리테일 매장에서 소비자 구매결정에 미치는 사회적 존재의 영향 -쇼핑동반자, 다른 고객, 판매원-)

  • Park, Kyungae
    • Journal of the Korean Society of Clothing and Textiles
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    • v.42 no.6
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    • pp.962-976
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    • 2018
  • This study examined: 1) the influence of 3 social presence types including shopping companions, other consumers, and sales associates on the consumer's purchase decision at a retail store; 2) the difference in the influence by shopping situation involving shopping together or shopping alone; and 3) the differences by consumer susceptibility to social influence and self-confidence. The study conducted three experiments with the retail shopping scenario manipulating consumer's positive self-evaluation, but lack of confidence after trying on a clothing product. Experiment 1 and Experiment 2 examined the positive influence of social presence while Experiment 3 examined the negative influence. The results showed that the positive comment of a shopping companion had the highest influence on the purchase decision. Such impact was more observable under the low susceptibility to normative influence. The negative comments of sales associate and shopping companion lowered the purchase decision. There was no difference by shopping situation. The results imply that influences of social presence on the consumer's purchase decision are different by positive or negative comments and such influences are not different by shopping situation.

A Study on New Alternatives for Overflowing Internet Information and Blocking Harmful Information (인터넷 정보과잉과 유해정보 차단을 위한 새로운 대안 연구)

  • Kim, Sang-Geun
    • Journal of Convergence for Information Technology
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    • v.9 no.10
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    • pp.81-86
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    • 2019
  • Problems related to information overload and harmful information have already expanded to national social problems as well as personal problems. This study explores the causes of Internet addiction, exposure to harmful information, malicious comments, fake information/information manipulation, and new alternatives that have recently been felt as social problems. Assuming that existing technologies/policies were not applied effectively, psychological cause analysis was performed for the fundamental problem approach. As a result, internal problems such as obsession with knowledge/understanding of wrong information/black and white stereotypes and prejudice were analyzed as main causes. Each proposed solution aims to help improve national technology/policy regarding internet addiction and blocking harmful information.

Understanding the Sentiment on Gig Economy: Good or Bad?

  • NORAZMI, Fatin Aimi Naemah;MAZLAN, Nur Syazwani;SAID, Rusmawati;OK RAHMAT, Rahmita Wirza
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.10
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    • pp.189-200
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    • 2022
  • The gig economy offers many advantages, such as flexibility, variety, independence, and lower cost. However, there are also safety concerns, lack of regulations, uncertainty, and unsatisfactory services, causing people to voice their opinion on social media. This paper aims to explore the sentiments of consumers concerning gig economy services (Grab, Foodpanda and Airbnb) through the analysis of social media. First, Vader Lexicon was used to classify the comments into positive, negative, and neutral sentiments. Then, the comments were further classified into three machine learning algorithms: Support Vector Machine, Light Gradient Boosted Machine, and Logistic Regression. Results suggested that gig economy services in Malaysia received more positive sentiments (52%) than negative sentiments (19%) and neutral sentiments (29%). Based on the three algorithms used in this research, LGBM has been the best model with the highest accuracy of 85%, while SVM has 84% and LR 82%. The results of this study proved the power of text mining and sentiment analysis in extracting business value and providing insight to businesses. Additionally, it aids gig managers and service providers in understanding clients' sentiments about their goods and services and making necessary adjustments to optimize satisfaction.

A Study of Male Subculture on Fashion Contents of YouTube - Focusing on Dick Hebdige's Subculture Theory - (유튜브 패션 콘텐츠에 표현된 남성 하위문화 연구 - 딕 햅디지의 하위문화 이론을 중심으로 -)

  • Park, Juha;Kim, Jongsun
    • Fashion & Textile Research Journal
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    • v.22 no.6
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    • pp.727-738
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    • 2020
  • This study focused on popular YouTube subculture content and male YouTuber characteristics. We conducted a case study on YouTube videos and viewer's comments of male YouTubers who interacted with subculture or fashion themes within YouTube. Based on Dick Hebdige's subculture theory, we categorized male subculture characteristics of style expression to show how YouTube plays a role in the formation of subculture. The representative types of male subculture were divided into metro sexual, adolescent boys, drag queen, and homosexual. YouTube simultaneously played a role in accumulating video viewing as well as indirect experiences in various communication activities and cultures among viewers. YouTube was used as a space for video producers as well as viewers and subscribers to discover and build identity. Subculture makes people aware of cultural diversity within society, and their doubles and lifestyles serve as important clues to track culture and fashion changes. This research is significant in the field of fashion media and subculture research due to its examination of male subculture phenomenon on YouTube based on an analysis of the video content of culture insiders and viewers' comments as well as immediate responses.

Signals' Influence on Crowd Funding Investment Decisions: A comparison of Taiwan and India

  • Md. Mukitul, Hoque;Sang-Joon, Lee
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.1
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    • pp.231-242
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    • 2023
  • Crowd funding faces a number of significant obstacles despite its rapid growth and popularity, with the main one being the possible asymmetric information between fundraisers and potential supporters. A study taxonomy based on signalling theory has been created to compare projects originating from Taiwan and India. This was made possible by obtaining a dataset from the crowd funding website, Kickstarter (Global platform). To make the project effective, the study's goal is to look into how signals (e.g., goal-setting, comments, and updates) might be used to reduce the problem of information asymmetry. Thus, we applied an Ordinary Least Squares (OLS) regression. Both Taiwan and India demonstrated signal mitigation of information asymmetry, but Taiwan showed a stronger relationship between ambitious goals and successful projects than India. The relative importance of project comments has been found to be stronger in Taiwan than in India; the relative importance of project updates has been found to be weaker and negatively correlated with project success in India, in contrast to Taiwan. Notably, our findings provide a theoretical and practical framework for understanding and using signals in successful crowd funding campaigns and activities in these two emerging countries.

TRIB: A Clustering and Visualization System for Responding comments on WebBlog (TRIB: 웹블로그 댓글분류 시각화 시스템)

  • Bae, Min-Jung;Lee, Yun-Jung;Ji, Jeong-Hoon;Woo, Gyun;Cho, Hwan-Gyu
    • Annual Conference of KIPS
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    • 2009.04a
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    • pp.226-229
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    • 2009
  • 최근 들어 인터넷 게시판이나 개인 블로그 등은 온라인상에서 사람들의 정보 공유나 의견 교환의 중요한 매체가 되고 있다. 많은 수의 블로그들은 현재 사회적으로 이슈가 되는 여러 문제들을 반영하고 있다. 또한 최근 댓글을 통해 적극적으로 자신의 의사 표현하거나 다른 사람들의 의견을 살피는 인터넷 사용자의 증가로 인터넷 뉴스나 블로그 기사에 많은 수의 댓글이 달리고 있다. 그러나 대부분의 블로그나 인터넷 포털 사이트의 경우 기사나 댓글들을 순차적인 목록 형태로 제공하므로 자신이 원하는 내용의 댓글을 검색하거나 전체 댓글에 대한 전반적인 파악은 힘든 일이다. 따라서 본 논문에서는 기사에 달린 많은 수의 댓글들을 분류하고, 이를 시각화 하는 시스템인 TRIB(Telescope for Responding comments for Internet Blog)을 제안한다. TRIB은 미리 정의된 사용자 정의 사전을 이용하여 댓글을 내용에 따라 분류하여 시각화 하므로 사용자들은 자신의 관심과 흥미에 따라 개인화 된 뷰를 볼 수 있다. 1,000개 이상의 댓글을 가진 뉴스 기사들을 대상으로 한 실험을 통해 TRIB 시스템의 댓글 분류와 시각화 성능을 보인다.

Distribution and Evaluation of News on Portals: How News Use and Engagement Influence Portal News Credibility

  • Najin JUN
    • Journal of Distribution Science
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    • v.21 no.7
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    • pp.1-9
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    • 2023
  • Purpose: This study aims to understand if heterogeneous news is evenly consumed and distributed on portals as it examines people's news use and engagement behaviors and news credibility. Focusing on the four behaviors of news use, i.e., viewing news by keyword search, viewing news from subscribed sources, viewing news from the list of most-viewed news, and reading comments, and the three behaviors of news engagement, i.e., sharing news, 'liking' or 'recommending' news, and posting comments, this study investigates the relation between each of the behaviors and portal news credibility. Research design, data and methodology: From 2022 News Audience Survey in Korea, this study conducts a regression analysis to investigate the relations between each behavior and news credibility. Results: The results show a positive relation for the former two news use behaviors and the latter two news engagement behaviors, and a negative relation for the latter two news use behaviors. Conclusions: The positive relations between active news use and engagement behaviors and portal news credibility indicate that news consumers are more likely to use and engage in attitude-consistent news rather than attitude-challenging news, implying that heterogeneous news is less likely to be consumed and distributed evenly on portals across all news users.

A Comparative Evaluation of Airline Service Quality Using Online Content Analysis: A Case Study of Korean vs. International Airlines

  • Peter Ractham;Alan Abrahams;Richard Gruss;Eojina Kim;Zachary Davis;Laddawan Kaewkitipong
    • Asia pacific journal of information systems
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    • v.31 no.4
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    • pp.491-526
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    • 2021
  • Airlines can employ a variety of quality monitoring procedures. In this study, we employ a content analysis of 8 years of online reviews for Korean airlines in contrast to other international airlines. Online airline reviews are infrequent, relative to the total number of passengers - the number of reviews is multiple orders of magnitude lower than passenger volumes - and online airline reviews are, therefore, not representative of passenger attitudes overall. Nevertheless, online reviews may be indicative of specific service issues, and draw attention to aspects that require further study by airline operators. Furthermore, significant words and phrases used in these airline reviews may help airline operators to rapidly automate filtering, partitioning, and analysis of incoming passenger comments via other channels, including email, social media posts, and call center transcripts. The current study provides insights into the contents of online reviews of Korean vs Other-International airlines, and opportunities for service enhancement. Further, we provide a set of marker words and phrases that may be helpful for management dashboards that require automated partitioning of passenger comments.

Exploring Public Opinion to Analyze the Consequences of Social Media on Students' Behaviors

  • Asif Nawaz;Tariq Ali;Saif Ur Rehman;Yaser Hafeez
    • International Journal of Computer Science & Network Security
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    • v.24 no.8
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    • pp.159-168
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    • 2024
  • Social media sites like as twitter, Facebook and flicker widely used by people, not only as a source of distributing information but also as for communication purpose, with the advancement of technology today. Now a day's one of the most frequently used communication methods are social networks. In various research studies, their use in different fields and the effects of social media on student's behaviors, chat sites and blogs caused by Facebook has been analyzed. In order to obtain the basic data, a general scanning model that is public opinion and views of parents and comments that are openly available across social media sites, used to perceive attitude of graduate students, instead of traditional methods like questionnaires and survey's conduction. A dataset of nearly 20000 reviews of parents was collected from different social media networks about their children's, while in another dataset in which 362 graduate school teachers who observe the students to use social media during classes, labs and in campus during free times, their comments about those students were chosen. As per this study, through different positive and negative factors the detailed analysis has been performed to show effect of social media on student's behavior.

Crowd Psychological and Emotional Computing Based on PSMU Algorithm

  • Bei He
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.8
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    • pp.2119-2136
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    • 2024
  • The rapid progress of social media allows more people to express their feelings and opinions online. Many data on social media contains people's emotional information, which can be used for people's psychological analysis and emotional calculation. This research is based on the simplified psychological scale algorithm of multi-theory integration. It aims to accurately analyze people's psychological emotion. According to the comparative analysis of algorithm performance, the results show that the highest recall rate of the algorithm in this study is 95%, while the highest recall rate of the item response theory algorithm and the social network analysis algorithm is 68% and 87%. The acceleration ratio and data volume of the research algorithm are analyzed. The results show that when 400,000 data are calculated in the Hadoop cluster and there are 8 nodes, the maximum acceleration ratio is 40%. When the data volume is 8GB, the maximum scale ratio of 8 nodes is 43%. Finally, we carried out an empirical analysis on the model that compute the population's psychological and emotional conditions. During the analysis, the psychological simplification scale algorithm was adopted and multiple theories were taken into account. Then, we collected negative comments and expressions about Japan's discharge of radioactive water in microblog and compared them with the trend derived by the model. The results were consistent. Therefore, this research model has achieved good results in the emotion classification of microblog comments.