• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.8
• /
• pp.2571-2586
• /
• 2022

The rapid popularity of government social media has generated huge amounts of text data, and the analysis of these data has gradually become the focus of digital government research. This study uses Python language to analyze the big data of the Chinese provincial government Weibo. First, this study uses a web crawler approach to collect and statistically describe over 360,000 data from 31 provincial government microblogs in China, covering the period from January 2018 to April 2022. Second, a word separation engine is constructed and these text data are analyzed using word cloud word frequencies as well as semantic relationships. Finally, the text data were analyzed for sentiment using natural language processing methods, and the text topics were studied using LDA algorithm. The results of this study show that, first, the number and scale of posts on the Chinese government Weibo have grown rapidly. Second, government Weibo has certain social attributes, and the epidemics, people's livelihood, and services have become the focus of government Weibo. Third, the contents of government Weibo account for more than 30% of negative sentiments. The classified topics show that the epidemics and epidemic prevention and control overshadowed the other topics, which inhibits the diversification of government Weibo.

• Iberoamérica
• /
• v.16 no.2
• /
• pp.151-188
• /
• 2014

This work aims to describe pragmatic strategies and linguistic features of replies that occur in the comment section of online newspapers. The dominant media in this digital age is the Internet and its rapid development and expansion of use have contributed not only to the change of the form of production of journalistic texts, but also to the consumption of those texts. In the past, the news was transmitted in a unidirectional way but now readers of online newspapers do not remain passively reading the articles. They actively participate in the exchange of opinions with other readers. The individual consumption of journalistic texts has become a collective and social act. The purpose of the study is to investigate the communication intention of the users of comment sections and analyze the linguistic formulation of replies. We attempt to discover specific aspects of replies and responses for online newspaper articles, considering them as an independent type of Computer Mediated Communication (Internet Mediated Communication). Observing language attitudes appearing in the electronic environment and discovering the characteristics of the Spanish language on the Internet will allow us to contribute to understand the theoretical aspects related to the CMO better.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.181-185
• /
• 2008

Recently, the Virtual Reality(VR) became one of the most powerful tools in making media files. In the field of engineering, while it is increasing to use 3D CAD model in the process of design to manufacturing, the VR is not popular in comparison with media business. XVL(eXtensible Virtual Reality Markup Language) is one of XML(eXtensible Markup Language) which is a standard web media language. XVL provides the connection between 3D CAD data and virtual reality, and it can be easily published through internet for the engineering purpose. In this study, a web based VR model for major components in a nuclear power plant has been developed by using XVL and corresponding 3D CAD data. The proposed model is expected to be used in the engineering field to cooperate among experts, and also, it will provide more plausible explanation to ordinary people.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.1
• /
• pp.391-406
• /
• 2015

Social media have emerged as new communication channels between consumers and companies that generate a large volume of unstructured text data. This social media content, which contains consumers' opinions and interests, is recognized as valuable material from which businesses can mine useful information; consequently, many researchers have reported on opinion-mining frameworks, methods, techniques, and tools for business intelligence over various industries. These studies sometimes focused on how to use opinion mining in business fields or emphasized methods of analyzing content to achieve results that are more accurate. They also considered how to visualize the results to ensure easier understanding. However, we found that such approaches are often technically complex and insufficiently user-friendly to help with business decisions and planning. Therefore, in this study we attempt to formulate a more comprehensive and practical methodology to conduct social media opinion mining and apply our methodology to a case study of the oldest instant noodle product in Korea. We also present graphical tools and visualized outputs that include volume and sentiment graphs, time-series graphs, a topic word cloud, a heat map, and a valence tree map with a classification. Our resources are from public-domain social media content such as blogs, forum messages, and news articles that we analyze with natural language processing, statistics, and graphics packages in the freeware R project environment. We believe our methodology and visualization outputs can provide a practical and reliable guide for immediate use, not just in the food industry but other industries as well.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.5
• /
• pp.423-443
• /
• 2009

We present the design and implementation of a unique sensing and actuation application -- the Illuminator: a sensor network-based intelligent light control system for entertainment and media production. Unlike most sensor network applications, which focus on sensing alone, a distinctive aspect of the Illuminator is that it closes the loop from light sensing to lighting control. We describe the Illuminator's design requirements, system architecture, algorithms, implementation and experimental results. The system uses the Illumimote, a multi-modal and high fidelity light sensor module well-suited for wireless sensor networks, to satisfy the high-performance light sensing requirements of entertainment and media production applications. The Illuminator system is a toolset to characterize the illumination profile of a deployed set of fixed position lights, generate desired lighting effects for moving targets (actors, scenic elements, etc.) based on user constraints expressed in a formal language, and to assist in the set up of lights to achieve the same illumination profile in multiple venues. After characterizing deployed lights, the Illuminator computes optimal light settings at run-time to achieve a user-specified actuation profile, using an optimization framework based on a genetic algorithm. Uniquely, it can use deployed sensors to incorporate changing ambient lighting conditions and moving targets into actuation. Experimental results demonstrate that the Illuminator handles various high-level user requirements and generates an optimal light actuation profile. These results suggest that the Illuminator system supports entertainment and media production applications.

• International Journal of Internet, Broadcasting and Communication
• /
• v.9 no.3
• /
• pp.59-69
• /
• 2017

The best 'hub' to communicate with the citizen is using social media to marketing the business. However, there has several issued and the most common issue that face in critical is a capital issue. This issue is always highlight because most of automatic sentiment detection tool for Facebook or any other social media price is expensive and they lack of technical skills in order to control the tool. Therefore, in directly they have some obstacle to get faster product's feedback from customers. Thus, the personal online retailing need to struggle to stay in market because they need to compete with successful online company such as G-market. Sentiment analysis also known as opinion mining. Aim of this research is develop the tool that allow user to automatic detect the sentiment comment on social media account. RAD model methodology is chosen since its have several phases could produce more activities and output. Soppy tool will be develop using Microsoft Visual. In order to generate an accurate sentiment detection, the functionality testing will be use to find the effectiveness of this Soppy tool. This proposed automated Soppy Tool would be able to provide a platform to measure the impact of the customer sentiment over the postings on their social media site. The results and findings from the impact measurement could then be use as a recommendation in the developing or reviewing to enhance the capability and the profit to their personal online retailing company.

• The Journal of the Korea Contents Association
• /
• v.11 no.6
• /
• pp.197-204
• /
• 2011

In line with the development of Media, the use of character has been developed in various ways. Specially, it has been emerged the functions of written language of visualization and delivery of emotion in the digitalized environment due to speedy growth of internet and Mobile. The emoticons emerged as a tool for the convenience of communication proved to have taken effective role in the part of communication culture. Particularly, Hangul emoticons which contains the meaning of communication and sharing in tandem with the principle of Hangul invention, provides convenience in combination & use due to its structural and design characteristic for which it plays a significant role of visual element. Hangul emoticon is definitely a part of Hangul culture and in view of globalization of visual language in connection with media development, there is a huge potential being to be used as a international communication tool. In this study, it will be reviewed on the increased utilization of Hangul emoticons and related public issues as being a part of typography media, in view of the generalization of private media as well as change of subjective user.

• International journal of advanced smart convergence
• /
• v.8 no.3
• /
• pp.167-176
• /
• 2019

Building skins are expanding even beyond theirfunctions as a simple boundary between the exterior and interior and into the realm of linguistic functions thanks to the development of media art. LED has been used as material on outer walls following the advancement of building materials, so the outerskins of large buildings are evolving into a messenger of language capable of communication. In big cities, buildings send out video images to enable communication between people and architecture, which plays a huge role in determining the identity of a building beyond simple advertising. Such media fa?ade technologies can be understood based on the concept of outerskin change, which refers to the idea that animals change the colors or textures of their skins to show their various states. In addition, various message delivery functions in human clothes should be included in such a discussion. We need to research on the possibilities of seeing media facades for their information delivery function and expanding them into information delivery between buildings as well as just between buildings and people.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.1-7
• /
• 2023

Since the first outbreak of COVID-19 in 2019, it has caused a huge blow to the restaurant industry. However, as social distancing was lifted as of April 2022, the restaurant industry gradually recovered, and as a result, interest in restaurant start-ups increased. Therefore, in this paper, big data analysis was conducted by selecting "restaurant start-up" as a key keyword through social media big data analysis using Textom and then conducting word frequency and CONCOR analysis. The collection period of keywords was selected from May 1, 2022 to May 23, 2023, after the lifting of social distancing due to COVID-19, and based on the analysis, the development of a restaurant start-up consulting chatbot service is proposed.

• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.206-211
• /
• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.