• The Journal of Information Systems
• /
• v.26 no.2
• /
• pp.85-104
• /
• 2017

Purpose The purpose of this study is to improve the efficiency of the activities of loosely connected network organization through the platform(Ba) of knowledge sharing. Loosely connected network organizations have been tried to promote new work and complement the scarce resources through collaborations. NPO(Non-Profit Organization) is essential to establish cooperation networks in order to achieve the public interest on the basis of scarce resources. This study interpreted the Ba on the 'Change-On' program and analyzed the social networks of regional organizations through the activation of the Ba. The 'Change-On' program is conducted for several years to promote the efficiency of the NPO network by Daum Generation Foundation. Design/methodology/approach This study made a design to organize the Ba concept of Nonaka & Konno and presented a case of the Ba activated based on the NPO network of regional order. According to the social network analysis of regional cooperation within the network of participating organizations was extended, it was found that the principal plays a significant role as a central hub made. Findings According to the empirical analysis, this study illustrated that various types of network were formed among NPOs based on the 'Change-On'. Furthermore, the networks surrounding NPOs are extended to the other people connected to them. This means that the network of NPOs had been diversified via the facilitation of the Ba. This study throws new highlights on the new role for the Ba as a network promoter in addition to the partner as a technology-provider in the NPO ecosystem. Moreover, the network analysis between before-and-after can be used for the evaluation of the effectiveness of the various Ba programs.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2004.05a
• /
• pp.544-547
• /
• 2004

Current increasingly information systems log historic information in a systematic way. Not only workflow management systems, but also ERP, CRM, SCM, and B2B systems often provide a so-called 'event log'. Unfortunately, the information in these event logs is rarely used to analyze the underlying processes. Process mining aims at improving this problem by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs. This paper focuses on the mining social networks. This is possible because event logs typically record information about the users executing the activities recorded in the log. To do this we combine concepts from workflow management and social network analysis. This paper introduces the approach and presents a tool to mine social networks from event logs.

• Asia-Pacific Journal of Business
• /
• v.15 no.1
• /
• pp.273-287
• /
• 2024

Purpose - This study conducts the co-occurrence analysis, one of the social network analysis using global OTA's online reviews and grades in order to understand the experience structure of foreign tourists visiting cutural tourism resources in Jeju, Korea. Design/methodology/approach - For this purpose, this study selects 6 cultural tourism resources in Jeju as the study sites, and collects qualitative review data (noun, adjectives, and verb) and quantitative grade data. Findings - The co-occurrence network analysis between words and grade of market and street shows that the grade of 5 appears the most simultaneous with pork, buy, lot, try, fresh, black, food, price, seafood, local, market, good, street, etc. and the grade of 1 connects with small, dish, better, taste, etc. And the co-occurrence network analysis between words and grade of tradition and folklore shows that the grade of 5 appears the most simultaneous with village, place, museum, visit, time, life, culture, women, diver, use, lot, etc. and the grade of 1 connects with minute, spend, room, recommend, honey, etc. Research implications or originality - The above research results are relevant in order to find out the core experience of foreign tourists using online review and grade generated by foreign tourists and use as the important information to develop the strategies related to the planning and management of cultural tourism resources.

• Asia pacific journal of information systems
• /
• v.29 no.3
• /
• pp.448-467
• /
• 2019

In a new age of smart tourism, free independent travelers (FITs) choose their travel routes in a more diversified and less predictable way with the aid of smart services. This paper focuses on the movements of Chinese outbound FITs in the U.S. in the year of 2018. 110 places to visit (destinations) extracted from 122 travel routes recommendations on Qyer.com, a major online travel community in China, are analyzed with social network analysis (SNA). Based on the results of SNA, employing degree centrality, eigenvector centrality, betweenness centrality, network visualization, and cluster diagram methods, some preferred cities and natural attractions outside city centers (i.e., New York City (NYC), Los Angeles, San Francisco, Washington D.C., and Niagara Falls) are identified. Moreover, it is found that NYC in the East and Los Angeles in the West play a major role in the movements of Chinese FITs. This study contributes to the body of knowledge on tourist destination movements and provides valuable implications for smart service development in the tourism and hospitality industry.

• The Journal of Society for e-Business Studies
• /
• v.21 no.1
• /
• pp.119-129
• /
• 2016

With the development of web, amount of information are generated in social web. Then many researchers are focused on the extracting and analyzing social issues from various social data. The proposed approach performed gathering the science data and analyzing with LDA algorithm. It generated the clusters which represent the social topics related to 'health'. As a result, we could deduce the relationship between science data and social issues.

• International Journal of Computer Science & Network Security
• /
• v.23 no.5
• /
• pp.1-6
• /
• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.178-185
• /
• 2021

The emergence of social networks has led to the flourishing of a new golden era of branding, which is a challenge for companies due to the need for creative positioning of companies with an emphasis on building trust and loyalty to the brand. Consumers are becoming more demanding and due to a wide range of products in different markets, make demands that are more stringent on companies. The goal of this article was to study the main trends of branding and advertising on social networks to develop a new approach to brand promotion. Methodology. The quantitative and qualitative research design was used to determine the main trends in branding and advertising on social networks. The methodology included the following methods: 1) analysis of the relationship between brand value and brand content strategy, 2) content analysis of the content of companies in social networks on the example of 10 world-famous brands with the highest value. The results allowed forming the criteria of effective content and communication: simplicity of content and simplicity of communication, lack of direct advertising of products, emphasis on global socio-economic problems and social orientation, unobtrusive communication, content creativity, indirect information about the product or work, the history of the company's development through various tools. The main content strategies of brands are defined: storytelling strategy; strategy of informing about the history of the company's development; entertainment and information strategy; strategy of joint interaction with the audience through the involvement of wellknown influencers or users of products. The theoretical and practical value of the results is confirmed by the conceptualization of the main content strategies of world-famous brands, which are pioneers in new ways to build relationships with users through social networks. The research proposes to use a customer-oriented approach to brand promotion. This means studying consumer behavior and predicting possible changes in behavior, which determines the level of interaction with the brand, the content strategy of the brand, and its effectiveness.

• The Journal of Information Systems
• /
• v.24 no.1
• /
• pp.147-168
• /
• 2015

Why people reduce or stop using social network services(SNS), which are regarded as a mean of relationship and communication, unlike the early trend? To explain the phenomenon, this study tries to predict psychological decision making process of users from perspectives of cognitive dissonance theory. From this perspective, this study attempted an integrative approach that reflected 'User's literacy' indicating the ability of individuals to use SNS, and 'negative mass media influence' such as media reports on side effects or the bad experiences of acquaintances, along with the 3 factors used in the SNS Prior research. This study conducted an empirical analysis by surveying 256 facebook users, and the major findings are as follows:- First, Social-overload, complexity, uncertainty and negative media influence are significantly affect dissonance on the use of SNS. Second, Dissonance on the use of SNS significantly affects the behavior that possibly reduces and limits the use of SNS. In other words, the users who have experienced psychological dissonance respond passively by avoiding the use of SNS to resolve the dissonance. Third, the moderating effect of User's literacy wasn't a significant. This study presents a clue to understand psychological decision making process of use of SNS and a guideline for establishing practical strategies. In addition, it is important to note that this study contributes to expansion of theoretical discussion about usage.

• The Journal of Information Systems
• /
• v.23 no.1
• /
• pp.93-109
• /
• 2014

This study aims to develop a rich understanding of user goals in user-empowering information technologies which have been dominating part in the information systems environment. A particular focus is on users' goals in a social network site (SNS) which is a typical example of user-empowering technologies. Users conduct various activities in order to achieve diverse goals in SNS. Thus, investigating what goals users pursue in SNS will give insights into understanding the users. We employed the laddering interview technique and means-end chain approach. Interviews of 50 Facebook users were analyzed to produce a hierarchical goal map showing users' goal structure. The map contains 18 goals, including self-reflection, psychological stability, belongingness, improving productivity, and amusement as ultimate goals in SNS. In the map, there are varied routes from activities to ultimate goals in SNS; that is, a complex assembly consisting of activities and goals. The findings call the information systems research community to have more interests in diverse goals and values users seek with technologies.

• International Journal of Computer Science & Network Security
• /
• v.24 no.8
• /
• pp.61-71
• /
• 2024

The dynamic nature of Online Social Networks (OSNs), especially on platforms like Twitter, presents challenges in identifying and responding to community attacks, particularly within Arabic content. The proposed integrated system addresses these challenges by achieving 91% accuracy in detecting real-time community event attacks while efficiently managing computational costs. This is accomplished through the use of specialized integrated approach clustering to detect both major and minor attacks. Additionally, the system leverages clustering algorithms, temporal modules, and social network graphs to identify events, map communities, and analyze online dynamics. An extensive parameter sensitivity analysis was conducted to fine-tune the algorithm, and the system's effectiveness was validated using a benchmark dataset, demonstrating substantial improvements in event detection.