• Title/Summary/Keyword: Social Media Buzz

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Effect of the Strength of Weak Ties & Emotional Perception on the Social Network Game's Diffusion (Strength of Weak Ties와 감성적 인식이 소셜네트워크게임(SNG)의 확산에 미치는 영향 연구)

  • Song, Myung-Bean;Yoo, Hyun-Gyu;Jo, Eun-Ae;Lee, Sang-Ho
    • Journal of Digital Convergence
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    • v.12 no.5
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    • pp.69-78
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    • 2014
  • This study deals with the digital policy proposal through the path modeling study on the effect of the strength of weak ties & emotional perception leading to the user's satisfaction, WOM between game users, and the verification on the effect of the emotional real name SNS on the social network game's diffusion. Researcher confirmed that the effect of the strength of weak ties & emotional perception led to the user's satisfaction, WOM of SNG. Even though weak tie, researchers estimate that the users emotionally interact with the real name relation effect of SNS. And effective factors for WOM are not a tie relationship or emotional interactivity of weak tie antecedently but user's satisfaction. As a result, though antecedent factors (weak tie & interactivity) had a positive effect as real name SNS, eventually powerful factor of making buzz was the SNG user's satisfaction. Thus researchers expect the practical policy proposition for government & corporation, which means SNG service providers more carefully manage the service satisfaction for WOM with SNG user's experience.

A Trend Analysis on E-sports using Social Big Data

  • Kyoung Ah YEO;Min Soo KIM
    • Journal of Sport and Applied Science
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    • v.8 no.1
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    • pp.11-17
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    • 2024
  • Purpose: The purpose of the study was to understand a trend of esports in terms of gamers' and fans' perceptions toward esports using social big data. Research design, data, and methodology: In this study, researchers first selected keywords related to esports. Then a total of 10,138 buzz data created at twitter, Facebook, news media, blogs, café and community between November 10, 2022 and November 19, 2023 were collected and analyzed with 'Textom', a big data solution. Results: The results of this study were as follows. Firstly, the news data's main articles were about competitions hosted by local governments and policies to revitalize the gaming industry. Secondly, As a result of esports analysis using Textom, there was a lot of interest in the adoption of the Hangzhou Asian Games as an official event and various esports competitions. As a result of the sentiment analysis, the positive content was related to the development potential of the esports industry, and the negative content was a discussion about the fundamental problem of whether esports is truly a sport. Thirdly, As a result of analyzing social big data on esports and the Olympics, there was hope that it would be adopted as an official event in the Olympics due to its adoption as an official event in the Hangzhou Asian Games. Conclusions: There was a positive opinion that the adoption of esports as an official Olympic event had positive content that could improve the quality of the game, and a negative opinion that games with actions that violate the Olympic spirit, such as murder and assault, should not be adopted as an official Olympic event. Further implications were discussed.

A domain-specific sentiment lexicon construction method for stock index directionality (주가지수 방향성 예측을 위한 도메인 맞춤형 감성사전 구축방안)

  • Kim, Jae-Bong;Kim, Hyoung-Joong
    • Journal of Digital Contents Society
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    • v.18 no.3
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    • pp.585-592
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    • 2017
  • As development of personal devices have made everyday use of internet much easier than before, it is getting generalized to find information and share it through the social media. In particular, communities specialized in each field have become so powerful that they can significantly influence our society. Finally, businesses and governments pay attentions to reflecting their opinions in their strategies. The stock market fluctuates with various factors of society. In order to consider social trends, many studies have tried making use of bigdata analysis on stock market researches as well as traditional approaches using buzz amount. In the example at the top, the studies using text data such as newspaper articles are being published. In this paper, we analyzed the post of 'Paxnet', a securities specialists' site, to supplement the limitation of the news. Based on this, we help researchers analyze the sentiment of investors by generating a domain-specific sentiment lexicon for the stock market.