• Journal of Korea Multimedia Society
• /
• v.19 no.2
• /
• pp.428-435
• /
• 2016

Hundreds of millions of new posts and information are being uploaded and propagated everyday on Online Social Networks(OSN) like Twitter, Facebook, or Instagram. This paper proposes and implements a GPS-location based SNS data mapping, analysis, and visualization system, called Smart SNS Map, which collects SNS data from Twitter and Instagram using hundreds of PlanetLab nodes distributed across the globe. Like no other previous systems, our system uniquely supports a variety of functions, including GPS-location based mapping of collected tweets and Instagram photos, keyword-based tweet or photo searching, real-time heat-map visualization of tweets and instagram photos, sentiment analysis, word cloud visualization, etc. Overall, a system like this, admittedly still in a prototype phase though, is expected to serve a role as a sort of social weather station sooner or later, which will help people understand what are happening around the SNS users, systems, society, and how they feel about them, as well as how they change over time and/or space.

• Journal of Contemporary Eastern Asia
• /
• v.14 no.1
• /
• pp.23-43
• /
• 2015

In most of the world, the current trend in information technology is for open data movement that promotes transparency and equal access. An opposite trend is observed in China, which has the world's largest Internet population. The country has implemented sophisticated cyber-infrastructure and practices under the name of The Golden Shield Project (commonly referred to as the Great Firewall) to limit access to popular international web services and to filter traffic containing 'undesirable' political content. Increasingly, tech-savvy Chinese bypass this firewall and use Twitter to share knowledge on censorship circumvention and encryption to collectively troubleshoot firewall evasion methods, and even mobilize actions that border on activism. Using a mixed mythological approach, the current study addresses such networked knowledge sharing among citizens in a restricted web ecosystem. On the theoretical front, this study uses webometric approaches to understand change agents and positive deviant in the diffusion of censorship circumvention technology. On policy-level, the study provides insights for Internet regulators and digital rights groups to help best utilize communication networks of positive deviants to counter Internet control.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.6
• /
• pp.2996-3011
• /
• 2017

With rapid growth of web technology and dissemination of smart devices, social networking service(SNS) is widely used. As a result, huge amount of data are generated from SNS such as Twitter, and sentiment analysis of SNS data is very important for various applications and services. In the existing sentiment analysis based on the $Na{\ddot{i}}ve$ Bayes algorithm, a same number of attributes is usually employed to estimate the weight of each class. Moreover, uncountable and meaningless attributes are included. This results in decreased accuracy of sentiment analysis. In this paper two methods are proposed to resolve these issues, which reflect the difference of the number of positive words and negative words in calculating the weights, and eliminate insignificant words in the feature selection step using Multinomial $Na{\ddot{i}}ve$ Bayes(MNB) algorithm. Performance comparison demonstrates that the proposed scheme significantly increases the accuracy compared to the existing Multivariate Bernoulli $Na{\ddot{i}}ve$ Bayes(BNB) algorithm and MNB scheme.

• Journal of Contemporary Eastern Asia
• /
• v.13 no.1
• /
• pp.69-81
• /
• 2014

While much in the field of public management has emphasized the importance of nonprofit advocacy activities in policy and decision-making procedures, few have considered the relevance and impact of leading actors on structuring diverse patterns of information sharing and communication through social media. Building nonprofit advocacy is a complicated process for a single organization to undertake, but social media applications such as Facebook and Twitter have facilitated nonprofit organizations and stakeholders to effectively share information and communicate with each other for identifying their mission as it relates to environmental issues. By analyzing the Australian Marine Conservation Society's (AMCS) Twitter network data from the period 1 April to 20 April, 2013, this research discovered diverse patterns in nonprofit advocacy by leading actors in building advocacy. Based on the webometrics approach, analysis results show that nonprofit advocacy through social media is structured by dynamic information flows and intercommunications among participants and followers of the AMCS. Also, the findings indicate that the news media and international and domestic nonprofit organizations have a leading role in building nonprofit advocacy by clustering with their followers.

• Journal of Information Technology Services
• /
• v.14 no.2
• /
• pp.143-158
• /
• 2015

Companies and governments in an era of big data have been tried to create new values with their data resources. Among many data resources, many companies especially pay attention to data which is obtained from Social Network Service (SNS) because it reveals precise opinion of customers and can be used to estimate profiles of them from their social relationships. However, it is not only hard to collect, store, and analyze the data, but system applications are also insufficient. Therefore, this study proposes a S-POS (Social POS) system which consists of three parts; Twitter Side, POS Side and TPAS (Twitter&POS Analysis System). In this system, SNS data and POS data which are collected from Twitter Side and POS Side are stored in Mongo D/B. And it provides several services with POS terminal based on analysis and matching results which are generated from TPAS. Through S-POS system, we expect to efficient and effective store and sales managements of system users. Moreover, they can provide some differentiated services such as cross-selling and personalized recommendation services.

• Genomics & Informatics
• /
• v.18 no.2
• /
• pp.17.1-17.4
• /
• 2020

The amount of content on social media platforms such as Twitter is expanding rapidly. Simultaneously, the lack of patient information seriously hinders the diagnosis and treatment of rare/intractable diseases. However, these patient communities are especially active on social media. Data from social media could serve as a source of patient-centric knowledge for these diseases complementary to the information collected in clinical settings and patient registries, and may also have potential for research use. To explore this question, we attempted to extract patient-centric knowledge from social media as a task for the 3-day Biomedical Linked Annotation Hackathon 6 (BLAH6). We selected amyotrophic lateral sclerosis and multiple sclerosis as use cases of rare and intractable diseases, respectively, and we extracted patient histories related to these health conditions from Twitter. Four diagnosed patients for each disease were selected. From the user timelines of these eight patients, we extracted tweets that might be related to health conditions. Based on our experiment, we show that our approach has considerable potential, although we identified problems that should be addressed in future attempts to mine information about rare/intractable diseases from Twitter.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.6
• /
• pp.3499-3511
• /
• 2014

This study examined what determinants affect the intention of retweeting on Twitter from the perspectives of motivations and social psychology. The primary theoretical foundations are the theory of reasoned action (TRA), motivation theory and social capital theory. An online survey was administrated to collect the data. The data collected was analyzed using the structural equation model (SEM). The findings showed that both the attitude toward the retweeting behavior and subjective norm have significant effects on the intention to retweet. The results also showed that the attitude toward the retweeting behaviors was influenced by the individual intrinsic motivation and the norm of reciprocity. Social trust also had a significant influence on the intention to retweet. This study discusses the implications of these findings.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.8
• /
• pp.377-384
• /
• 2016

Our goal is to build the system which collects tweets from Twitter, analyzes the sentiment of each tweet, and helps users build a sentiment tagged corpus semi-automatically. After collecting tweets with the Twitter API, we analyzes the sentiments of them with a sentiment dictionary. With the proposed system, users can verify the results of the system and can insert new sentimental words or dependency relations where sentiment information exist. Sentiment information is tagged with the JSON structure which is useful for building or accessing the corpus. With a test set, the system shows about 76% on the accuracy in analysing the sentiments of sentences as positive, neutral, or negative.

• The Journal of Information Systems
• /
• v.23 no.4
• /
• pp.1-24
• /
• 2014

This study is intended to examine two issues related with social media messages. At first, the authors investigate that how they can categorize messages in the social media and how corporate twitters and brand twitters communicate with consumers. Secondly, after dividing messages in the social media into several groups, the authors investigate how each type of messages differ one another in terms of the consumer response. For examining these research issues, the authors gather twitter message data of global top 100 brands and categorize messages into 5 types (i.e., interactivity, diversion, information sharing, promotional, content) based on the motivation of communication and the format of the messages. Especially, the authors use content analysis methodology, which is normally used as the qualitative approach, in order to identify the type of messages. Furthermore, the authors present interactivity type of messages can communicate better with consumers and induce more favorable responses from consumers in the social media than any other type of messages. This research can provide implications in terms of theoretical, methodological, and managerial perspective.

• Journal of Advanced Navigation Technology
• /
• v.16 no.1
• /
• pp.82-88
• /
• 2012

In recent years, social awareness and concern about the SNS is getting a lot and many researches on the social impact of the SNS and variety strategies using SNS have emerged one after another. In this paper, we explain the method of interlocking between SNS and variety sensors in physical computing environment. Especially we propose that interlocking technology between sensors and twitter in Arduino platform(open source environment) can be used for the handicapped people. We design a way to send message via twitter for handicapped people using values from various sensors.