969 resultados para social intelligence


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With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users’ personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0.

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Purpose - Researchers debate whether tacit knowledge sharing through Information Technology (IT) is actually possible. However, with the advent of social web tools, it has been argued that most shortcomings of tacit knowledge sharing are likely to disappear. This paper has two purposes: firstly, to demonstrate the existing debates in the literature regarding tacit knowledge sharing using IT, and secondly, to identify key research gaps that lay the foundations for future research into tacit knowledge sharing using social web. Design/methodology/approach - This paper reviews current literature on IT-mediated tacit knowledge sharing and opens a discussion on tacit knowledge sharing through the use of social web. Findings - First, the existing schools of thoughts in regards to IT ability for tacit knowledge sharing are introduced. Next, difficulties of sharing tacit knowledge through the use of IT are discussed. Then, potentials and pitfalls of social web tools are presented. Finally, the paper concludes that whilst there are significant theoretical arguments supporting that the social web facilitates tacit knowledge sharing there is a lack of empirical evidence to support these arguments and further work is required. Research limitations/implications - The limitations of the review includes: covering only papers that were published in English, issues of access to full texts of some resources, possibility of missing some resources due to search strings used or limited coverage of databases searched. Originality/value - The paper contributes to the fast growing literature on the intersection of KM and IT particularly by focusing on tacit knowledge sharing in social media space. The paper highlights the need for further studies in this area by discussing the current situation in the literature and disclosing the emerging questions and gaps for future studies.

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Large communities built around social media on the Internet offer an opportunity to augment analytical customer relationship management (CRM) strategies. The purpose of this paper is to provide direction to advance the conceptual design of business intelligence (BI) systems for implementing CRM strategies. After introducing social CRM and social BI as emerging fields of research, the authors match CRM strategies with a re-engineered conceptual data model of Facebook in order to illustrate the strategic value of these data. Subsequently, the authors design a multi-dimensional data model for social BI and demonstrate its applicability by designing management reports in a retail scenario. Building on the service blueprinting framework, the authors propose a structured research agenda for the emerging field of social BI.

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Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

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Background and Objectives: Although depression is a commonly occurring mental illness, research concerning strategies for early detection and prophylaxis has not until now focused on the possible utility of measures of Emotional Intelligence (EI) as a potential predictive factor. The current study aimed to investigate the relationship between EI and a clinical diagnosis of depression in a cohort of adults. Methods: Sixty-two patients (59.70% female) with a DSM-IV-TR diagnosis of a major affective disorder and 39 aged matched controls (56.40% female) completed self-report instruments assessing EI and depression in a cross-sectional study. Results: Significant associations were observed between severity of depression and the EI dimensions of Emotional Management (r = -0.56) and Emotional Control (r = -0.62). The results show a reduced social involvement, an increased prior institutionalization and an increased incidence of "Schizophrenic Psychosis" and "Abnormal Personalities" in the sub-group of repeated admissions. Conclusions: Measures of EI may have predictive value in terms of early identification of those at risk for developing depression. The current study points to the potential value of conducting further studies of a prospective nature.

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The rise of the mobile internet enables the creation of applications that provide new and easier ways for people to organise themselves, raise issues, take action and interact with their city. At the same time, society faces new problems that can only be solved when citizens work together. Nevertheless, a lack of motivation or knowledge often prevents many citizens from regularly contributing to the common good. In this position paper, we present DoGood – a mobile app – as a socio-technological system that aims at supporting the collective intelligence of citizens in their pursuit of civic engagement and civic collaboratories. Our study asks to what extent gamification can motivate users to “do good” deeds. The DoGood app uses gamified elements to encourage citizens to submit and promote their civic activities as well as to join the activities of others. Gamification is sometimes criticised for simply adding a limited number of game elements, such as leaderboards, on top of an existing experience with the hope of increasing motivation. However, in the case of the DoGood app, the process of game design was an integral part of the development, and the gamified elements target the user’s intrinsic motivations instead of providing them with an external reward. In this paper, we present design elements of the app and discuss their potential to support collective intelligence for the common good.

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Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated be fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. Thes parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.

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Purpose: Emotional intelligence (EI) is an increasingly important aspect of a health professional’s skill set. It is strongly associated with empathy, reflection and resilience; all key aspects of radiotherapy practice. Previous work in other disciplines has formed contradictory conclusions concerning development of EI over time. This study aimed to determine the extent to which EI can develop during a radiotherapy undergraduate course and identify factors affecting this. Methods and materials: This study used anonymous coded Likert-style surveys to gather longitudinal data from radiotherapy students relating to a range of self-perceived EI traits during their 3-year degree. Data were gathered at various points throughout the course from the whole cohort. Results: A total of 26 students provided data with 14 completing the full series of datasets. There was a 17·2% increase in self-reported EI score with a p-value<0·0001. Social awareness and relationship skills exhibited the greatest increase in scores compared with self-awareness. Variance of scores decreased over time; there was a reduced change in EI for mature students who tended to have higher initial scores. EI increase was most evident immediately after clinical placements. Conclusions: Radiotherapy students increase their EI scores during a 3-year course. Students reported higher levels of EI immediately after their clinical placement; radiotherapy curricula should seek to maximise on these learning opportunities.

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The aim of this paper is to propose design principles for ambient intelligence (AmI) environments. The question we are investigating is how these environments can be designed to support a group to be able to carry out common goal-oriented activities. The approach we are taking in answering this question is informed by the concept of collective intelligence (CI). We are applying the concept of CI to AmI as we have found it works well in biological and social systems. Examples from nature demonstrate the power of CI stimulated by implicit cues in the environment. We use these examples to derive design principles for AmI environments. By applying these design principles to a concrete scenario, we are able to propose ways to help decrease environmental pollution within urban areas.

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The realization of the ambient intelligence (AmI) vision will have a profound impact on our everyday lives and society. AmI applied in contexts like homes or public spaces will not only affect individual users but influence entire groups of users. The question is how we can apply such technologies to persuade groups and individual users. Our approach is to design AmI environments by borrowing a concept which works very well in biological and social systems: Collective Intelligence (CI). The intelligence of a group surpasses the individual intelligences and leads to improved problem solving capabilities of individuals and groups. From nature we borrow examples of cues in the environment to stimulate goal directed collective intelligence (perCues). The application of perCues in AmI environments helps to persuade users to reach a common goal like decreasing environmental pollution. Adopting CI for AmI we blaze a trail for the design of persuasive AmI environments.

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Corporate executives require relevant and intelligent business information in real-time to take strategic decisions. They require the freedom to access this information anywhere and anytime. There is a need to extend this functionality beyond the office and on the fingertips of the decision makers. Mobile Business Intelligence Tool (MBIT) aims to provide these features in a flexible and cost-efficient manner. This paper describes the detailed architecture of MBIT to overcome the limitations of existing mobile business intelligence tools. Further, a detailed implementation framework is presented to realize the design. This research highlights the benefits of using service oriented architecture to design flexible and platform independent mobile business applications. © 2009 IEEE.

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Resumen: El artículo plantea una lectura transversal del Documento de la Comisión Teológica Internacional, titulado “En busca de una ética universal: una nueva mirada sobre la ley natural” de tal manera que, a partir del reconocimiento de una ley natural que subyace a toda norma, se procura mostrar cómo esa convicción no impide la participación de los cristianos en el diálogo social. El autor señala las paradojas a las que conduce la ética de la discusión y el lugar de la discusión pública como estímulo para alcanzar la verdad. Enfatiza la importancia del amor a la verdad como condición necesaria para que una sociedad sea noble y respetable. Considera el lugar del diálogo y el consenso y la existencia de una verdad última que la inteligencia puede captar en el marco de un sano pluralismo. También aborda la relación entre este pluralismo y las religiones y su contribución al debate público.

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Este trabalho aproxima as contribuições da teoria das representações sociais e dos estudos em memória social para a compreensão do campo religioso, especificamente o Espiritismo, reconhecendo a importância da recordação de personalidades para a dinâmica religiosa. Esta pesquisa objetiva analisar o conteúdo da representação social de perfeição, o conteúdo e estrutura da memória de personalidades do Espiritismo e a relação entre ambos. Trata-se de estudo descritivo, desenvolvido em duas etapas. Participaram 75 participantes auto-declarados espíritas - 38 na primeira etapa e 37 na segunda, sendo entrevistados 24 desses. Os participantes, em média, possuíam 37,3 anos de idade e 16,7 anos como espíritas. Na primeira fase aplicou-se, através da Internet, a técnica de evocações livres com o termo indutor espíritos superiores, na qual os participantes respondiam que pessoas se associavam ao termo. Na segunda, prosseguiu-se com as evocações livres e questionário, para caracterização dos participantes. A partir das doze personalidades mais lembradas, realizou-se entrevista semi-estruturada, com questões sobre características, virtudes, lembranças, hierarquia das personalidades, e questões sobre o significado da perfeição e como alcançá-la. Os dados das evocações foram analisados através das técnicas do quadro de quatro casas e construção de árvore máxima de similitude. As entrevistas foram analisadas mediante análise categorial temática. Assim, verificou-se que as personalidades mais recordadas foram: Chico Xavier, Jesus, Allan Kardec, Emmanuel, Bezerra de Menezes, Madre Teresa de Calcutá, Joanna de Ângelis, Gandhi, André Luiz, Francisco de Assis, Maria de Nazaré e Divaldo P. Franco. A representação social de perfeição foi expressa, de modo simplificado, na sentença: um caminho, difícil e longo, em que o ser humano sai da sua condição de inferioridade para a perfeição, através do conhecimento (proveniente do trabalho, do estudo e do auto-conhecimento), livrando-se do seu egoísmo e expressando o amor, tal como demonstrado e vivido por Jesus. Verificou-se, ainda, que essas memórias se organizam, principalmente, em dois modelos de valores complementares no Espiritismo: 1) conhecimento, inteligência, razão, estudo, livro e 2) amor, vivência, fé, trabalho, exemplo. Eles se constituem nas duas condições essenciais para se alcançar essa perfeição. O primeiro modelo está principalmente personificado na figura de Allan Kardec e o segundo, em Jesus. Nesse sentido, o Espiritismo opera na mente dos fiéis, uma síntese entre ambos os modelos, tendo em Chico Xavier a personificação dessa síntese, constituindo-se como tipo ideal de espírita.

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In recent decades, numerous studies have shown a significant increase in violence during childhood and adolescence. These data suggest the importance of implementing programs to prevent and reduce violent behavior. The study aimed to design a program of emotional intelligence (El) for adolescents and to assess its effects on variables related to violence prevention. The possible differential effect of the program on both genders was also examined. The sample comprised 148 adolescents aged from 13 to 16 years. The study used an experimental design with repeated pretest-posttest measures and control groups. To measure the variables, four assessment instruments were administered before and after the program, as well as in the follow-up phase (1 year after the conclusion of the intervention). The program consisted of 20 one-hour sessions. The pretest-posttest ANCOVAs showed that the program significantly increased: (1) El (attention, clarity, emotional repair); (2) assertive cognitive social interaction strategies; (3) internal control of anger; and (4) the cognitive ability to analyze negative feelings. In the follow-up phase, the positive effects of the intervention were generally maintained and, moreover, the use of aggressive strategies as an interpersonal conflict-resolution technique was significantly reduced. Regarding the effect of the program on both genders, the change was very similar, but the boys increased assertive social interaction strategies, attention, and emotional clarity significantly more than the girls. The importance of implementing programs to promote socio-emotional development and prevent violence is discussed.