• Journal of Information Technology Applications and Management
• /
• v.17 no.4
• /
• pp.1-17
• /
• 2010

As web technologies evolve and so-called Web 2.0 technologies appear, collective intelligence is being applied in widespread areas. In general, mass collective intelligence like Wikipedia is created, revised, and managed by anonymous participants in an uncontrolled system. Thus, the knowledge provided by mass collective intelligence may be distorted, and may not be true, which may affect the user acceptance behavior. However, there have been few academic studies that analyzed the factors that affect user acceptance of mass collective intelligence, and their relationships. Under this academic background, we develop a model to examine how mass collective intelligence is accepted by users. The theoretical model is validated through an online survey of the Wikipedia users from three universities in Korea. The results reveal that the users will have positive attitude towards adopting mass collective knowledge when they perceive that the knowledge from mass collective intelligence is useful. We also find that the perceived usefulness of the knowledge is affected by perceived knowledge quality and trust in knowledge contributors. The results also suggest that perceived knowledge quality is determined by perceived level of collaboration, perceived objectivity, and recipient expertise, whereas trust in knowledge contributors is determined by natural propensity to trust and perceived objectivity. Theoretical and practical implications about mass collective knowledge are discussed.

• Educational Technology International
• /
• v.9 no.1
• /
• pp.49-77
• /
• 2008

As clearly suggested in the case of Wikipedia, collective intelligence is predicted to develop into the most important platform of knowledge and information in the future society. But it just remains at the level of activities for group projects in the present frame of education and so it doesn't lead to creating collective intelligence. This study looks into an 'information repository model of collective intelligence' that makes it possible to deliver an education process a priori of Shared Knowledge Reservoir to "Junior Digital Nomad", who is definitely and will be in existence, and that further enables them to be active there in reality. Based on this storage model, it suggests a practicable web system model; Junior Maphistory e-encyclopedia, which is appropriately consistent with the features of Web 2.0 and can grow into a general historical and geographical information service.

• The Journal of Information Systems
• /
• v.20 no.4
• /
• pp.1-22
• /
• 2011

This study addressed trust to collective intelligence for explaining the affecting factors to the intention to use of collective intelligence by dividing the object of trust into a Web site and an information source group. We explored the factors affecting user's continuance intention toward collective intelligence in the view off trust building. We made a well-structured survey of our proposed model and gained 205 cases. We analyzed the proposed research model empirically using partial least square method. The findings are summarized as follows. First, all key factors (relevance, timeless, completeness, understandability) composing of collective intelligence quality have a positive and significant impact on confirmation. Second, confirmation has a significant impact on trust toward a Web site, as well as toward an information source group. The last is that trust toward a Web site influences on continuance intention, whereas trust toward an information source group doesn't.

• Journal of Distribution Science
• /
• v.13 no.5
• /
• pp.113-120
• /
• 2015

Purpose - As the rapid development of ICT has been made recently, many domestic companies are trying to introduce smart work infrastructure. The purpose of institution of smart work is to enhance their performance. To this end, it is necessary to advance the way of working. Developing employees' collective intelligence should be regarded as a prerequisite for advancing the way of working. Job satisfaction of the employees is another important factor to enhance organizational performance. So this study aims to provide the theoretical background of systematic approach to smart work quality by empirically analyzing the effect of smart work quality on collective intelligence and job satisfaction. Research design, data, and methodology - A structural equation model was designed to examine cause-and-effect relationships among three latent variables(smart work quality, collective intelligence, job satisfaction). Three hypotheses were formulated. The first hypothesis is that the effect of smart work quality on collective intelligence will be positively and statistically significant. Likewise, the second hypothesis is that the effect of smart work quality on job satisfaction will be positively and statistically significant. Finally, the third hypothesis is that the effect of collective intelligence on job satisfaction will be positively and statistically significant. Based on the previous researches, 34 questionnaire items were developed to measure the effect of the three variables. The survey was conducted on 162 employees who are working under smart work environment. The number of the effective questionnaires for the analysis was 154. PASW Statistics 18 and AMOS 18 were used for the statistical analysis. Results - The validity and reliability test for questionnaire items have been carried out. From the factor analysis, 1 out of 34 items was eliminated. As a result, 33 out of 34 items were used for analyzing. The values of Cronbach's α ranged from 0.701 to 0.910, indicating the acceptable reliability of the questionnaire items. The values of χ2, df, CFI, TLI, RMSEA of the model are 102.838, 51, 0.949, 0.935, 0.082, respectively. So the structural equation model was statistically significant. The first and third hypotheses were supported. But the second hypothesis was rejected. Conclusions - An analysis using structural equation model showed meaningful implications about the effect of smart work quality on collective intelligence and job satisfaction. First, as the five quality elements of the smart work improved, the level of collective intelligence increased. Second, the statistical analysis showed smart work didn't have a direct effect on job satisfaction, which is inconsistent with the prior findings. The main purpose of smart work is to help achieve greater performance. The companies also need to make efforts to improve job satisfaction of their employees along with achieving greater performance. Third, an organization with higher level of collective intelligence showed greater job satisfaction. The companies under smart work environment need to develop functions to encourage participation, sharing, openness, and collaboration. This research will provide useful information for the companies which want to introduce smart work, distribution information system, management information system, etc.

• The Journal of Korean Association of Computer Education
• /
• v.14 no.2
• /
• pp.23-32
• /
• 2011

The Internet is appearing a new paradigm called Web 2.0 which 'Participation', 'Sharing', 'Openness', 'Cooperation'. Web 2.0 is expanded by experts and general users and many people's ideas can solve more problems than an expert's idea. The collective intelligence is techniques that express the valuable of Web 2.0. For this reason, the collective intelligence has attracted attention because of its potential as an educational tool. The purpose of this study is to develop a PBL-based programming instruction model using collective intelligence to improve students' problem solving abilities and programming attitudes and verified its effectiveness. As a result, the developed instruction model showed significant differences in the students' problem solving abilities and programming attitudes. According to these results, these have been proved that a PBL-based programming instruction model using collective intelligence has an influence to the students' problem solving abilities and programming attitudes.

• The Journal of Korean Association of Computer Education
• /
• v.15 no.2
• /
• pp.37-45
• /
• 2012

The case of South Korea's Internet newspapers, harmful advertising is illegal but rampant. The children and youth are not protected, so effective measures are urgently required. Therefore, to achieve self-regulation, a discrimination system model using collective intelligence and collective emotions is proposed. This study is to suggest a Discrimination System Model of harmful contents using collective intelligence and collective emotions as the actual program of self-regulation. The Discrimination System model forms the level of harmful contents by using contents, form, text, size as well as the implied and reminiscent story of image as discriminant factors of a group testing. The formed level is established for harmful contents discriminant criteria after going through the process of generalization again. It can be not clear and ambiguous for internet newspaper banner ads to be measure the level of harmfulness. This Discrimination System will have the strengths of resolving this problem.

• The Journal of the Korea Contents Association
• /
• v.15 no.2
• /
• pp.529-541
• /
• 2015

Collaborative learning of collective intelligence-based model is also ideal in higher education did not yet consensus still in the theoretical level. To become collective intelligence-based collaborative learning is to mobilize the competence of the various members should be promoted as much as possible with their own services designed to actively participate in and contribute to the goals of the joint. Is still based collaborative learning model of collective intelligence, which does the actual model is not developed in education is a key program in creative fusion judge called talent. The evolution of the main features of the house just in shaping the content of a modern lecture geureohagi need to check from time to time to see and pay attention. As part of this study, attempts were associated with the tvN planning and attention to trying connector Executive Lecture show "Creative Club 199" content. Well oriented intention to converge the needs of the times, but it is even more compelling naeeotda implement the collective intelligence based on 'how' the reality is that together with the participants.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.10
• /
• pp.1698-1711
• /
• 2011

Knowledge is often represented as a set of rules or a semantic network in intelligent systems. Recently, ontology has been widely used to represent semantic knowledge, because it organizes thesaurus and hierarchal information between concepts in a particular domain. However, it is not easy to collect semantic relationships among concepts. Much time and expense are incurred in ontology construction. Collective intelligence can be a good alternative approach to solve these problems. In this paper, we propose a collective intelligence approach of Games With A Purpose (GWAP) to collect various semantic resources, such as words and word-senses. We detail how to construct the semantic information model or ontology from the collected semantic resources, constructing a system named FunWords. FunWords is a Korean lexical-based semantic resource collection tool. Experiments demonstrated the resources were grouped as common nouns, abstract nouns, adjective and neologism. Finally, we analyzed their characteristics, acquiring the semantic relationships noted above. Common nouns, with structural semantic relationships, such as hypernym and hyponym, are highlighted. Abstract nouns, with descriptive and characteristic semantic relationships, such as synonym and antonym are underlined. Adjectives, with such semantic relationships, as description and status, illustration - for example, color and sound - are expressed more. Last, neologism, with the semantic relationships, such as description and characteristics, are emphasized. Weighting the semantic relationships with these characteristics can help reduce time and cost, because it need not consider unnecessary or slightly related factors. This can improve the expressive power, such as readability, concentrating on the weighted characteristics. Our proposal to collect semantic resources from the collective intelligence approach of GWAP (our FunWords) and to weight their semantic relationship can help construct the semantic information model or ontology would be a more effective and expressive alternative.

• International Journal of Contents
• /
• v.8 no.3
• /
• pp.1-6
• /
• 2012

This study establishes a simple Causal Map in order to understand the structure of Social Network Services(SNS). From this, the paper proposes a simulation with drawing Simulation Model and it examines whether a Dunbar Number is available for the emergence of collective intelligence based on an on-line network. Through my analytical research, it turn out both Closed SNS and Open SNS have their own Dunbar Number. However, it appear that Open SNS can expand infinitely as it has a unique property namely weak tie. This implies that it is significant for a system or policy to be developed in order to overcome the problem of Dunbar Number, whereas restricting the extension of a network by considering the Dunbar Number would have a negative impact on emergence of collective intelligence.

• Journal of Information Technology Services
• /
• v.21 no.1
• /
• pp.103-125
• /
• 2022

This study empirically examines the correlation between the data, system, service quality, collective intelligence, innovation activity, and work performance of the KMS for employees of state-run enterprises. This study also confirmed that collective intelligence and innovation activity have a mediating effect on the relationship between KMS system quality and work performance. For this study, employees of state-run enterprises completed a 5-point Likert scale survey, and the data obtained were analyzed with descriptive statistics. The reliability and validity of variables were also verified through a measurement model analysis. Structural equation modeling of IBM SPSS 26 and AMOS 26 were used to prove the hypothesis. Through this study, For the improvement of sustainable work performance of state-run enterprises, which is a difficult issue to solve, not only should the quality of the KMS utilized in the enterprises be improved and managed, but also the design for various incentive schemes tailored to the enterprises' job characteristics, such as rewards, HR bonus, work incentives, job allowance, and encouragement from the head of the enterprise, should be reviewed and continuously developed in reflection of the active collective intelligence of the employees and the effect of innovation activities. Then, the work performance of public institutions will increase.