• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1224-1230
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• 2014

Because Twitter provides an easy way to reweet and reply to other user's tweets, it is used to delivery our opinion to others and get useful information from followers as a useful tool. Recently, there have been many attempts to use Twitter in many application area. Especially, Twitter has been tried to use in education area. Twitter service can be used in educational environments as a communication tool between professor and students and among students without restriction on space and time. Twitter service has good possibility of applying, but there have not been many studies that prove the effectiveness and possibility of the tool as a useful educational tool through experimental studies. In this study, Twitter is used as a tool of the question-and- answer session of the university students during a semester. And the activities are investigated and analyzed. As the results of the analysis, if we do not force the use of Twitter, Twitter utilization of students is low. Thus, we show that Twitter has the potential for educational utilizing, but the aggressive efforts between professor and students are needed to show such effects.

• Journal of Multimedia Information System
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• v.2 no.3
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• pp.287-294
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• 2015

We are living in epoch of information when Internet touches all aspects of our lives. Therefore, it provides a plenty of services each of which benefits people in different ways. Electronic Mail (E-mail), File Transfer Protocol (FTP), Voice/Video Communication, Search Engines are bright examples of Internet services. Between them Social Network Services (SNS) continuously gain its popularity over the past years. Most popular SNSs like Facebook, Weibo and Twitter generate millions of data every minute. Twitter is one of SNS which allows its users post short instant messages. They, 100 million, posted 340 million tweets per day (2012)[1]. Often big amount of data contains lots of noisy data which can be defined as uninteresting and unclassifiable data. However, researchers can take advantage of such huge information in order to analyze and extract meaningful and interesting features. The way to collect SNS data as well as tweets is handled by crawlers. Twitter crawler has recently emerged as a great tool to crawl Twitter data as well as tweets. In this project, we develop Twitter Crawler system which enables us to extract Twitter data. We implemented our system in Java language along with MySQL. We use Twitter4J which is a java library for communicating with Twitter API. The application, first, connects to Twitter API, then retrieves tweets, and stores them into database. We also develop crawling strategies to efficiently extract tweets in terms of time and amount.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1107-1115
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• 2016

Efficient Market Hypothesis (EMH), states that at any point in time in a liquid market security prices fully reflect all available information. This paper presents a study of proving the hypothesis through daily Twitter sentiments using the hybrid approach of the lexicon-based approach and the naïve Bayes classifier. In this research we analyze the currency exchange rate movement of Indonesia Rupiah vs US dollar as a way of testing the Efficient Market Hypothesis. In order to find a correlation between the prediction sentiments from Twitter data and the actual currency exchange rate trends we collect Twitter data every day and compute the overall sentiment to label them as positive or negative. Experimental results have shown 69% correct prediction of sentiment analysis and 65.7% correlation with positive sentiments. This implies that EMH is semi-strong Efficient Market Hypothesis, and that public information provide by Twitter sentiment correlate with changes in the exchange market trends.

• Journal of Fashion Business
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• v.15 no.1
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• pp.158-170
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• 2011

The purpose of this study was to examine how recently fashion corporate did use SNS applications for their product promotion strategies as case studies, and to provide what kinds of SNS marketing strategies would be developed for fashion corporate. Specifically, this study was focused on Twitter among SNS applications. For this study, Internet webs, news paper, articles, and other press work were used for resources. Five fashion corporate such as Buckaroo, MLB, North Faces, Kolon, and ABC Mart were analyzed. As the results, first, fashion corporate used Twitter as the marketing tool for their product promotion. Second, they tried to make an increase the numbers of Twitter follower from their customers. Third, Twitter was used for making higher customer loyalty by fashion corporate through a variety of program such as special events, game, music, or viral marketing. However, there were still some limitations on fashion corporate's Twitter usage, compared to other non-fashion corporate. Thus, fashion corporate needs to provide more creative and unique Twitter marketing strategies. Therefore, based on these results, fashion brand merchandising marketing strategies of fashion products would be provided from this study.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.546-553
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• 2011

Every day 60 million emails are sent out around the world. IT technology has given us so many ways of communicating. Technology such as twitter has the potential to give us more than just an opportunity to tell others what happened in our day. If we understand and appreciate what twitter is capable of, we can use it to instantly share our lives with others. In this paper, we introduce to the trend of web and social networks, mini blog and twitter services of digital new media age. Finally, we proposed a strategy of application for the social media and the direction of growth for twitter.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.910-919
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• 2012

We have observed huge success in social network services like Facebook and Twitter, and many researchers have done their analysis on these services. As massive data observed by users is produced on Twitter, many researchers have been conducting research to detect an event on Twitter. Some of them developed a system to detect the earthquakes or to find the local festivals. However, they did not consider the credibility of location information on Twitter although their systems were using the location information. In this paper, we analyze the credibility of the profile location and the correlation between the spatial attributes on Twitter as the preliminary research of the event detection system on Twitter. We analyzed 0.5 million Twitter users in Korea and 2.8 million users around the world. 49.73% of the users in Korea and 90.64% of the users in the world posted tweets in their profile locations. This paper will be helpful to understand the credibility of the spatial attributes on Twitter when the researchers develop an application using them.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.588-600
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• 2019

Each year Malaria affects over 200 million people worldwide. Particularly, African continent is highly hit by this disease. According to many researches, this continent is ideal for Anopheles mosquitoes which transmit Malaria parasites to thrive. Rainfall volume is one of the major factor favoring the development of these Anopheles in the tropical Sub-Sahara Africa (SSA). However, the surveillance, monitoring and reporting of this epidemic is still poor and bureaucratic only. In our paper, we proposed a method to fast monitor and report Malaria instances by using Social Network Systems (SNS) and precipitation volume in Nigeria. We used Twitter search Application Programming Interface (API) to live-stream Twitter messages mentioning Malaria, preprocessed those Tweets and classified them into Malaria cases in Nigeria by using Support Vector Machine (SVM) classification algorithm and compared those Malaria cases with average precipitation volume. The comparison yielded a correlation of 0.75 between Malaria cases recorded by using Twitter and average precipitations in Nigeria. To ensure the certainty of our classification algorithm, we used an oversampling technique and eliminated the imbalance in our training Tweets.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.879-886
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• 2018

The basic search engine on Twitter shows not only tweets that contain search keywords, but also all articles written by users with nicknames containing search keywords. Since the tweets unrelated to the search keyword are exposed as search results, it is inconvenient to many users who want to search only tweets that include the keyword. To solve this inconvenience, this study improved the search function of Twitter by developing an algorithm that searches only tweets that contain search keywords. The improved functionality is implemented as a Web service using ASP.NET MVC5 and is available to many users. We used a powerful collection method in C# to retrieve the results of an object, and it was also possible to output them according to the number of 'retweets' or 'favorites'. If the number of retrieved numbers is less than a given number, we also added an exclusion filter function. Thus, sorting search results by the number of retweets or favorites, user can quickly search for opinions that are of interest to many users. It is expected that many users and data analysts will find the developed function convenient to search on Twitter.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.112-119
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• 2021

Social media has become a global means of communication in people's lives. Most people are using Twitter for communication purposes and its inappropriate use, which has negative effects on people's lives. One of the widely common misuses of Twitter is cyberbullying. As the resources of dialectal Arabic are rare, so for cyberbullying most people are using dialectal Arabic. For this reason, the ultimate goal of this study is to detect and classify cyberbullying on Twitter in the Arabic context in Saudi Arabia. To help in the detection and classification of tweets, Pointwise Mutual Information (PMI) to generate a lexicon, and Support Vector Machine (SVM) algorithms are used. The evaluation is performed on both methods in terms of the F1-score. However, the F1-score after applying the PMI is 50%, while after the SVM application on the resampling data it is 82%. The analysis of the results shows that the SVM algorithm outperforms better.

• Asia Marketing Journal
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• v.21 no.2
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• pp.73-98
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• 2019

As information and communication technology continue its remarkable development, the exchange of information online becomes as prevalent and frequent as face-to-face communication in daily life. Therefore, the management and application of WOM (word of mouth) practices will become more important than ever to companies. Currently, there are various types of communication channels for online WOM, and each channel has its own unique traits. Most of the previous research studies online WOM by examining the information inside a single communication channel, but this research chooses two different communication channels and analyzes the effects of online WOM with each channel's unique characteristics. More specifically, this research focuses on the expectation that the effects of information from Twitter and blogs on product sales may differ because Twitter and blogs, two different communication channels for online WOM, have their own unique traits. Our particular aim is to perform an in-depth examination on the effects of communication channel's volume and valence on product sales, two important attributes of online WOM. Furthermore, while most of the empirical research focuses on online WOM and analyzes its effect on markets of temporary experience goods, such as movies and books, this research highlights focuses on the automobile market, a durable goods market. The results of our analysis are as follows: First, regarding blogs, a positive valence significantly and positively affects the sales of products, and this result indicates that consumers are influenced more by the emotional aspect of a product presented in a post than by the number of blog posts. Second, regarding Twitter, the volume of online WOM significantly and positively affects sales, an indication that as the number of posts increase, the sales increase. Through this research, we suggest that even those firms that sell durable goods can increase sales through the management and application of online WOM. Moreover, according to the characteristics of communication channels, the effects of online WOM on sales differ. As a practical implication of this research, we suggest that companies can and should create marketing strategies appropriate to their targeted communication channels.