• Title/Summary/Keyword: Tweet Function

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Influence on the Tweet Credibility and Attitude Toward Tweet of Tweet Content, Function and Involvement (트윗의 내용과 기능 그리고 관여도가 트윗 신뢰도와 태도에 미치는 영향)

  • Lee, Hyun-Ji;Chung, Donghun
    • The Journal of the Korea Contents Association
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    • v.13 no.6
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    • pp.137-147
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    • 2013
  • The purpose of this study is to examine what variables influence on tweet credibility and attitude toward tweet. For this, the present research used the tweet content(information/opinion), tweet function(without URL and RT/URL/RT) and involvement(low/hight) as independent variables and applied a triangular research design which are in-depth interview, survey and computer usability testing software. Main findings are as follows. First, the participants read tweets listed in order regardless of tweet content, function and involvement. Second, there was a significant main effect of the tweet content on the tweet credibility and an interaction effect of those three independent variables on the attitude toward tweet. Finally, the in-depth interview showed that information is perceived to be more credible than opinion and URL>RT>just information or opinion are listed in order on the tweet credibility.

Discovery of Urban Area and Spatial Distribution of City Population using Geo-located Tweet Data (위치기반 트윗 데이터를 이용한 도심권 추정과 인구의 공간분포 분석)

  • Kim, Tae Kyu;Lee, Jin Kyu;Cho, Jae Hee
    • Journal of Information Technology Services
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    • v.18 no.1
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    • pp.131-140
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    • 2019
  • This study compares and analyzes the spatial distribution of people in two cities using location information in twitter data. The target cities were selected as Paris, a traditional tourist city, and Dubai, a tourist city that has recently attracted attention. The data was collected over 123 days in 2016 and 125 days in 2018. We compared the spatial distribution of two cities according to the two periods and residence status. In this study, we have found a hot place using a spatial statistical model called dart-shaped space division and estimated the urban area by reflecting the distribution of tweet population. And we visualized it as a CDF (cumulative distribution function) curve so that the distance between all the tweets' occurrence points and the city center point can be compared for different cities.

An Analysis of IT Trends Using Tweet Data (트윗 데이터를 활용한 IT 트렌드 분석)

  • Yi, Jin Baek;Lee, Choong Kwon;Cha, Kyung Jin
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.143-159
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    • 2015
  • Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

The Study on the Public Typology based on Twitter's Political Opinion Analysis: Focusing on 10.26 by-election of Mayor of Seoul (트위터에서 형성된 정치적 의견 분석을 통한 분화된 공중 연구: 10.26 서울시장 재보궐 선거를 중심으로)

  • Hong, Ju-Hyun;Lee, Chang-Hyun
    • Korean journal of communication and information
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    • v.59
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    • pp.138-161
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    • 2012
  • This study is designed to explore the function of Twitter as a campaign platform during election campaign. For exploring the function of Twitter the form of tweet, the type of information on tweet and the way of opinion expression via Twitter were discussed by content analysis. This study finds, first, that, netizens express their opoinion of candidates without foundation and with emotional reactions. Second, they showed somewhat conflictive reactions according to their supporting candidates. This study conceptualized various kinds of public as 'blindly support public,' and 'blindly opposition public' in case of Park's supporters, 'rational support public,' and 'critical opposition public' in case of Na's supporters. Third, Park's supporters debated Na candidate's attitude of debate and her appearance blindly without foundation. Na's supporters argued Park's attitude of debate and his ignorance of Seoul Metropolitan government's policy blindly without foundation. Finally, this study discussed the relationship between the political discourse according to netizens' supporting via Twitter and the results of election. Park whose supporters attacked the opposing candidate by blaming her appearance and her attitude of debate won the election. Na didn't overcome her negative images. For her Twitter functioned as a media which is spreading negative factors about her. In conclusion, Twitter as a campaign platform during election times plays a key role in discussing candidates. However, netizens need to express their opinions with foundation and the candidates have to consider negative issue management. This study highlights the importance of peripheral factors which have a decisive effect on the results of election. The results of this study is useful for building political campaign strategy by candidates.

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