Extended architecture of knowledge management system with Web 2.0 technologies

Knowledge management systems (KMS) become increasingly important in periods of crises and economic slowdown, as many organizations are forced to lay off people, to reduce research and ICT budgets, to restructure departments and to optimize their costs. Subsequently, organizational knowledge assets, and mainly the existing tacit knowledge are threatened. This raises the importance of technologies that could assist organizational efforts to capture the existing knowledge and to mobilize it in order to overcome the crisis. Knowledge management systems should respond to these expectations and enable organizations dynamically to acquire and profit from all sources of knowledge. The present paper discusses the opportunities provided by extended KMS architecture combining elements of Web 2.0 technologies. It considers how Web 2.0 technologies can increase organizational effectiveness, efficiency and usability for company KM. The main services provided by KMS are identified and ranked. Finally, the paper makes an overview of the issue how KMS can enable companies to transform risks of the crises to new opportunities for further development

Models of webcasts and webinars: towards interactive new-media webcasts.

In this paper we provide a context for models of webcasts and webinars from the perspective of a UK higher education Institution and the corporate training setting. Our synthesis of technical and pedagogic elements arises from these e-learning and marketing considerations and forms a proposal for the Interactive New-media Webcast design (INWeb). Three webcast models are compared with respect to moderated text discussion, the presenterʼs capacity and the type of content engagement for the online event as a key component of the new design model. These e-learning webcast models are triangulated with Garrisonʼs (2004) distance learning historical timeline and Pincasʼ (2007) collection of pedagogic designs known as the 3Ps (Presentation, Practice and Performance). A critique of our mini-case studies is our way to ground the e-learning theory in real-world examples of use. These webcast illustrations are presented from both a business and academic perspective. Mooreʼs (1993, 1996) Transactional Distance Theory (TDT) is critically reviewed for its application to the pedagogic design of the INWeb model. Dialogue and structure are analysed to see the impact on the autonomous learner as a webcast participant. The transactional distance between the webcast presenter and the online viewer/ callers is explored in the context of the webcast content as a learner-generated Web 2.0 dynamic resource for learning and marketing. Our summary reflections then discuss how the current webcast models may be extended if we provide a framework informed by the Evolutionary Graph Theory and Metcalfeʼs Law (Hendler, 2008) as possible theoretical positions to tie together the professional social network and Web 2.0 elements to future interactive New-media Webcast Designs

The next generation of the web: an organisational perspective

The web has revolutionised information sharing, management, interoperability and knowledge discovery. The union of the two prominent web frameworks, Web 2.0 and the Semantic Web is often referred to as Web 3.0. This paper explores the basics behind the two paradigms, assesses their influence over organisational change and considers their effectiveness in supporting innovative solutions. It then outlines the challenges of combining the two web paradigms to form Web 3.0 and critically evaluates the impact that Web 3.0 will have on the social organisation. The research carried out follows action research principles and adopts an investigative and reviewing approach to the emerging trends and patterns that develop from the web's changing use, examining the underpinning enabling technologies that facilitate access, innovation and organisational change

Sentiment Analysis Meets Semantic Analysis: Constructing Insight Knowledge Bases

Numerous Web 2.0 applications collect user opinions, and other user-generated content in the form of product reviews, discussion boards, and blogs, which are often captured as unstructured data. Text mining techniques are important for analyzing users’ opinions (sentiment analysis) and identifying topics of interest (semantic analysis). However, little work has been carried out that combines semantics with user’s sentiments. This research proposes a Sentiment-Semantic Framework that incorporates results from both semantic and sentiment analysis to construct a knowledge base of insights gained from integrating the information extracted from each type of analysis. To evaluate the framework, a prototype is developed and applied to two different domains (e-commerce and politics) and the resulting insight knowledge bases constructed

A State of the Art on Social Network Analysis and its Applications on a Semantic Web

The increasingly popular web 2.0 sites provide the largest social network ever analyzed - users are now considered as plain web resources. Some researchers apply classical methods of social network analysis to such networks; others provide models to leverage the semantics of their representation. We present a state of the art of these two approaches and propose an architecture to merge and exploit the best features of each

Semantic Social Network Analysis

International audienceSocial Network Analysis (SNA) tries to understand and exploit the key features of social networks in order to manage their life cycle and predict their evolution. Increasingly popular web 2.0 sites are forming huge social network. Classical methods from social network analysis (SNA) have been applied to such online networks. In this paper, we propose leveraging semantic web technologies to merge and exploit the best features of each domain. We present how to facilitate and enhance the analysis of online social networks, exploiting the power of semantic social network analysis

Semantic Social Network Analysis

International audienceSocial Network Analysis (SNA) tries to understand and exploit the key features of social networks in order to manage their life cycle and predict their evolution. Increasingly popular web 2.0 sites are forming huge social network. Classical methods from social network analysis (SNA) have been applied to such online networks. In this paper, we propose leveraging semantic web technologies to merge and exploit the best features of each domain. We present how to facilitate and enhance the analysis of online social networks, exploiting the power of semantic social network analysis

Spontaneous diffusion of information in online social networks

Online Social Networks (OSN) are new types of web services which provide online communities an environment to gather and meet virtually. The online users are connected to each other via links of trust and utilize the features of the OSN to interact and communicate in an easy socio-technical way. Hence these virtual networks of social relationships have a high potential for influential decision-making and the word of mouth spread of information, but also for spreading fads, rumors, and erroneous information. The power of these new forms of social networks is also recognized by service providers, marketers and vendors of consumer goods. They would all like to (mis) use these existing communication channels to spread product placements, advertising and promotions directly to the connected users. However, just like the old economy businesses, not all attempted marketing initiatives are successful. Most of them fail or do notreach the desired audience. This paper tries to explain why OSN are a good environment for spontaneous diffusion of information and what phases of development need to beaccomplished to reach the optimal spreading rate for one piece information. Therefore, we start with a look at the "Hype Cycle" model of Gartner to explain over-enthusiasm for new technology adoptions. Next we introduce the concept of "social contagion" and the infections spread of information. After a short introduction of OSN, we try to illustrate the phases of a social online contagion development process which can lead to spontaneous and uncontrolled diffusion of information, messages or ideas. The core statement of our approach is that online individuals tend to behave collectively if they observe the virtual behaviors and actions of others. This principle of "other-directedness" can generate a chain reaction of infectious imitation which can sometimes spread uncontrolled through the interconnected social network like an epidemic. This helps to explain why some online information waves can grow extraordinarily high and others fall.Онлайнові соціальні мережі (ОСМ) є новими типами веб-сервісів, які пропонують онлайновим суспільствам середовище для гуртування та віртуального спілкування. Як наслідок, такі віртуальні мережі соціальних зв'язків мають високий потенціал для впливового прийняття рішень та розповсюдження інформації "з вуст в уста", але, з іншого боку, вони також можуть розповсюджувати чутки, плітки та некоректну інформацію. Потенціал цих мереж також розпізнається сервіс-провайдерами, маркетологами та виробниками товарів. Вони усі бажають використовувати ці існуючі комунікаційні канали для розповсюдження реклами продуктів безпосередньо користувачам. Але не усі такі спроби є успішними. Ця робота робить спробу пояснити, чому ОСМ є добрим середовищем для спонтанного розповсюдження інформації, та які етапи повинні бути виконані для досягнення оптимального рівня розповсюдження для одного елемента інформації. Ми починаємо з розгляду моделі гіперциклів Гартнера, яка пояснює надмірний ентузіазм при впровадженні нових технологій. Далі ми вводимо концепцію "соціального забруднення" та інфекційного розповсюдження інформації. Базова ідея нашого підходу полягає в тому, що онлайнові індивідуали прихильні до колективної поведінки, тобто вони спрямовані на віртуальну поведінку та дії інших. Цей принцип "спрямованості на інших" може генерувати ланцюгову реакцію інфекційних імітацій які інколи можуть розповсюджуватись неконтрольовано через соціальні мережі, подібно до епідемії