• Title/Summary/Keyword: Microblogging

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A Research on Usage Factors of Mobile Microblogging Service (모바일 마이크로블로깅(Mobile Microblogging) 서비스의 사용요인에 관한 연구)

  • Jin, Jeong-Suk;Lusi, Zhao;Park, Joo-Seok
    • Korean Management Science Review
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    • v.28 no.3
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    • pp.83-94
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    • 2011
  • Microblogging is a Web2.0 technology that is used to manage online interpersonal relationship in SNS. Microblogging service allows the users to publish online brief text updates, usually less than 140~200 characters, sometimes images too. Recently, it becomes more and more popular. There are many reasons, the major one of which is that it can be perfectly combined with mobile. Based on technology acceptance model (TAM) and according to mobile service and microblogging service, this research adds four attributes : Perceived enjoyment, Habit, Mobility, Social Influence. It studies the factors that will impact on the way in which people use rapid developing Mobile Microblogging Service. This research will compare the influence factors and intension to use with the results from other studies with SNS and Mobile Microblogging Service, and then conclude the differences that can be generated in Microblogging.

Microblogging Sentiment Investor, Return and Volatility in the COVID-19 Era: Indonesian Stock Exchange

  • FARISKA, Putri;NUGRAHA, Nugraha;PUTERA, Ika;ROHANDI, Mochamad Malik Akbar;FARISKA, Putri
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.3
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    • pp.61-67
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    • 2021
  • The covid-19 pandemic scenario caused the most extensive economic shocks the world has experienced in decades. Maintaining financial performance and economic stability is essential during the pandemic period. In these conditions, where movement is severely restricted, media consumption is considered to be increasing. The social media platform is one of the media online used by the public as a source of information and also expressing their sentiment, including individual investors in the capital market as social media users. Twitter is one of the social media microblogging platforms used by individual investors to share their opinion and get information. This study aims to determine whether microblogging sentiment investors can predict the capital market during pandemics. To analyze microblogging sentiment investors, we classified sentiment using the phyton text mining algorithm and Naïve Bayesian text classification into level positive, negative, and neutral from November 2019 to November 2020. This study was on 68 listed companies on the Indonesia stock exchange. A Vector Autoregression and Impulse Response is applied to capture short and long-term impacts along with a causal relationship. We found that microblogging sentiment investor has a significant impact on stock returns and volatility and vice-versa. Also, the response due to shocks is convergent, and microblogging investors in Indonesia are categorized as a "news-watcher" investor.

The Effect of Customer Participation Behavior on Brand Loyalty via B2C Microblogging (B2C 트위터를 통한 고객참여행위가 기업충성도에 미치는 영향)

  • Park, Jongpil
    • Journal of the Korean Operations Research and Management Science Society
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    • v.38 no.1
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    • pp.69-87
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    • 2013
  • Recently a large number of people have been using social networking and microblogging services such as Facebook and Twitter. These mediums play a pivotal communication channel in a business-to-customer (B2C) relationship. Given its importance in today's business, companies have invested in the strategic application of social network services to reach out to customers. This study provides a blueprint for mechanisms for successful execution of social network services in the context of developing an effective B2C relationship, such as customer participation behavior. The S-O-R(Stimulus-Organism-Response) framework lays out the foundation for developing our research model and provides a structured view for understanding customer participation behavior on brand loyalty. For the methodology, this study employed a mixed-method approach. Additionally, in order to provide empirical evidences, a total of 121 respondents have completed the survey. All the data were compiled and analyzed through structural equation modeling and were implemented in partial least square (PLS). To sum up, this study presented theoretical and practical implications by providing the effect of customer participation behavior on brand loyalty through B2C microblogging.

A case study on the effect of real-time microblogging activities in offline lecture environments (오프라인 강의식 수업에서 실시간 마이크로블로그 활용 학습활동 효과 사례분석)

  • Lim, Keol
    • Journal of Digital Contents Society
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    • v.12 no.2
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    • pp.195-203
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    • 2011
  • In-person lectures have structural issues that active communications in the classroom are limited because of the environments where the instructor usually delivers learning contents in a unilateral manner. Therefore, microcontents activities using real-time microblogging were suggested as complementary measures for the lecture in this study. Fourteen students in K University participated in the learning activity for eight weeks using a microblog during instructions. As a result, it was found that participants' positive learning activities increased by producing and collaborating ideas through real-time microblogging. Based on the results, suggestions were made as follows: strategies for the attention to the class, quality management of microcontents, and the development of blended learning design should be more studied further.

Disaster Events Detection using Twitter Data

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • v.9 no.1
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    • pp.69-73
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    • 2011
  • Twitter is a microblogging service that allows its user to share short messages called tweets with each other. All the tweets are visible on a public timeline. These tweets have the valuable geospatial component and particularly time critical events. In this paper, our interest is in the rapid detection of disaster events such as tsunami, tornadoes, forest fires, and earthquakes. We describe the detection system of disaster events and show the way to detect a target event from Twitter data. This research examines the three disasters during the same time period and compares Twitter activity and Internet news on Google. A significant result from this research is that emergency detection could begin using microblogging service.

Information Dissemination Model of Microblogging with Internet Marketers

  • Xu, Dongliang;Pan, Jingchang;Wang, Bailing;Liu, Meng;Kang, Qinma
    • Journal of Information Processing Systems
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    • v.15 no.4
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    • pp.853-864
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    • 2019
  • Microblogging services (such as Twitter) are the representative information communication networks during the Web 2.0 era, which have gained remarkable popularity. Weibo has become a popular platform for information dissemination in online social networks due to its large number of users. In this study, a microblog information dissemination model is presented. Related concepts are introduced and analyzed based on the dynamic model of infectious disease, and new influencing factors are proposed to improve the susceptible-infective-removal (SIR) information dissemination model. Correlation analysis is conducted on the existing information dissemination risk and the rumor dissemination model of microblog. In this study, web hyper is used to model rumor dissemination. Finally, the experimental results illustrate the effectiveness of the method in reducing the rumor dissemination of microblogs.

Classifying Temporal Topics with Similar Patterns on Twitter

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • v.9 no.3
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    • pp.295-300
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    • 2011
  • Twitter is a popular microblogging service that enables the users to send and read short text messages. These messages are becoming source to analyze topic trends and identify relations among temporal topics. In this paper, we propose a method to classify the temporal topics on Twitter as a problem of grouping the similar patterns. To provide a starting point for a classification under the same topics, we identify the content word weighting scheme based on Latent Dirichlet Allocation (LDA). And we formulate how the temporal topics in the time window can be classified like peaky topics, constant topics, and periodic topics. We provide different real case studies which show the validity of the proposed method. Evaluations show that the proposed method is useful as a classifying model in the analysis of the temporal topics.

Analysis and Implications of Twitter Data during the 2012 Election

  • Yun, Hongwon
    • Journal of Korea Society of Industrial Information Systems
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    • v.19 no.6
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    • pp.7-13
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    • 2014
  • Twitter is a microblogging service that allows users to post short messages on a variety of topics in real-time. In this work, we analyze Twitter messages posted during the 2012 elections and find those implications. This study uses Twitter messages related to the 2012 South Korean presidential campaign. The three main candidates are represented by the abbreviations A, M, and P. According to the statistical analysis, the number of tweets and re-tweets for candidate P was relatively stable over the entire campaign period. Candidate P had the highest percentage of terms related to elections pledges, and candidates A and M were judged to be a little bit poorer with respect to campaign promises. The positive terms ratio for candidate P was higher than those for the other two candidates. The negative terms ratio in the Twitter messages of P was considerably smaller than those of candidates A and M. After considering all these results, it is suggested cautiously that Twitter messages posted during an election campaign could be correlated with the outcome of the election.

More than popularity matters: How would voters like to get social networking with candidates?

  • Chang, Shao-Liang;Chen, Chi-Ying
    • International Journal of Advanced Culture Technology
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    • v.3 no.2
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    • pp.50-57
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    • 2015
  • An online survey was conducted to assess motivations for using, reliance on, and perceived credibility of political blogs and microblogs during both the Taiwanese general election of 2009 (the blog epoch) and the presidential elections of 2012 (the microblog epoch). Results indicated higher reliance on and motivation for using political blogs than microblogs. Blogs were also perceived to be more credible than microblogs. Respondents who primarily engaged in blogging for information purposes were more likely to judge candidate blogs as highly credible, whereas interest in entertainment emerged as the strongest predictor of the perceived credibility of microblogs. This research also provided quantitative evidence showing how users viewed blogs and microblogs differently in the context of political campaigns. The aim is to explore the pros and cons of blogging and microblogging as a tool for political communication.

Understanding Customer Participation Behavior via B2C Microblogging (B2C 마이크로블로깅을 통한 고객참여 메커니즘의 이해)

  • Park, Jongpil;Son, Jai-Yeol
    • Asia pacific journal of information systems
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    • v.22 no.4
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    • pp.51-73
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    • 2012
  • Social network services based on openness, connectedness, and mass participation are reshaping many aspects of how companies conduct business and create value for their customers. For instance, Facebook and Twitter are expected to play a pivotal role as a new communication channel through which companies-forge close relationships with their customers for co-creation of value for mutual benefits. Given the potential of social network services, it is not surprising that many companies have strategically invested in social network services to reach out to customers. Despite the growing interest in social network services as a platform to connect companies and their customers, few guidelines exist about how managers can effectively utilize social network services in forging relationships with their customers. As such, scholars should pay greater attention to how firms can successfully develop relationships with their customers on social network services. In particular, this study employs the S-O-R (stimulus-organism-response) framework as a theoretical lens to develop a research model that explains customers' participation in the value co-creation platform that companies opened on Twitter. According to the S-O-R framework, certain types of individuals' behaviors can be best understood based on a causal link from environmental stimulus to organism, and response. We apply the S-O-R framework to understand how ubiquitous connectivity (stimuli) can influence customers' experience (organism) with companies on Twitter, which in turn influence their participation behavior (response). Two steps have been undertaken to empirically test the research model. First, we conducted a content analysis of tweets written by customers who follow companies on Twitter. As a result, we found event/promotion participation, company support, and giving feedback as three specific types of customer participation behavior. Second, we conducted a web-based survey to test research hypotheses in the research model. Participations in the survey were solicited to customers who followed companies on Twitter. As a result, a total of 115 respondents have completed the survey. Data were analyzed using the partial least square (PLS) technique. The results of data analysis suggest that ubiquitous connectivity (stimuli) had strong positive effects on perceive usefulness, perceived enjoyment, and perceived intimacy (organism). Perceived intimacy showed positive effects on customer participation behavior (response), such as event participation, company support, and giving feedback. Perceived enjoyment was found to have strong positive effects on company support and giving feedback. On the other hand, perceived usefulness did not have significant impacts on the three types of customer participation behavior.

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