Employee positioning and workload allocation

Assigning tasks to employees is a difficult task. Errors committed in such assignments can have far-reaching consequences, such as reduced efficiency due to absenteeism, lack of job satisfaction, formal grievances, and generally deteriorating labor relations. This paper approaches the problem from a spatial point of view. First, the employees and the relevant tasks are mapped in a skill space. After feasible task assignments are determined, tasks are assigned to employees so as to minimize employee—task distances in order to avoid boredom, and minimize disequity between the individual employees’ workloads, and minimize costs. Computational results are provided for an engineering department of the Pontificia Universidad Católica de Chile in Santiago, Chile.     

Indoor Mobile Robotics at Grima, PUC

This paper describes the main activities and achievements of our research group on Machine Intelligence and Robotics (Grima) at the Computer Science Department, Pontificia Universidad Catolica de Chile (PUC). Since 2002, we have been developing an active research in the area of indoor autonomous social robots. Our main focus has been the cognitive side of Robotics, where we have developed algorithms for autonomous navigation using wheeled robots, scene recognition using vision and 3D range sensors, and social behaviors using Markov Decision Processes, among others. As a distinguishing feature, in our research we have followed a probabilistic approach, deeply rooted in machine learning and Bayesian statistical techniques. Among our main achievements are an increasing list of publications in main Robotics conference and journals, and the consolidation of a research group with more than 25 people among full-time professors, visiting researchers, and graduate students.     

基于两级传播理论的舆论超网络传播分析

社交网络挖掘可以使人们更好地认识信息在网络中的传播规律,分析信息在事件中的传播特点。现有的文献研究主要集中于舆论事件社交网络的静态建模,以及针对一些共性特点的仿真验证,而对舆论事件模型结构变化的讨论较少。本文尝试从两级传播理论出发,采用三层超网络结构对舆论事件不同时段构建传播分析模型,给出舆论演化分析度量指标,挖掘超网络结构变化的特点,探索舆论酝酿期积蓄力量的潜在因素。以长生疫苗事件进行分析,发现需要在酝酿期有多样化的意见领袖不断在各个话题中进行牵引,在积累了潜在的舆论人群之后才能促成舆论爆发。     

Predicting Attitudes Toward Knowledge Sharing by E-Mail: An Empirical Study

Social influence factors in sharing knowledge by e-mail are important issues in developing and understanding successful knowledge management systems and human–computer interaction. This article investigates important factors in shaping attitudes toward knowledge sharing by e-mail, based on social influence theory and self-determination theory. An empirical test of the proposed model using an online survey was conducted with a sample of undergraduate college students who use group e-mails for class assignments (n?=?566). All social influence factors significantly influenced attitudes toward knowledge sharing by e-mail (R ² = .57). Information systems researchers and practitioners will be able to more fully understand the roles of social influence factors in developing and designing knowledge management.     

A pedagogical model to develop teaching skills. The collaborative learning experience in the Immersive Virtual World TYMMI

The initial training of quality teachers is seen as a key to improving the learning outcomes of students in Chile. The TYMMI project is one of the initiatives being developed to provide a space for simulation for teaching practices in immersive virtual environments in Second Life and Open Sim. Initial Teachers Training belong to the School of Education at the Universidad Católica de la Santísima Concepción, participated during 2014 in the implementation of challenges, based on a pedagogical model and teaching strategies such as role play and problem-based learning. Through direct observation and blogs, the results show that participants have an important domain in the pedagogical and technological interaction. Despite the perception of the technical difficulties of using platforms, students emphasize that the experience has been supportive along their teaching practices, and it has allowed them to reinforce subject content, which poses a very motivating intellectual and technological challenge.     

Social Media Analysis and Public Opinion: The 2010 UK General Election

Social media monitoring in politics can be understood by situating it in theories of public opinion. The multimethod study we present here indicates how social media monitoring allow for analysis of social dynamics through which opinions form and shift. Analysis of media coverage from the 2010 UK General Election demonstrates that social media are now being equated with public opinion by political journalists. We use interviews with pollsters, social media researchers and journalists to examine the perceived link between social media and public opinion. In light of competing understandings these interviews reveal, we argue for a broadening of the definition of public opinion to include its social dimension.     

Socially rational agents in spatial land use planning: A heuristic proposal based negotiation mechanism

This paper introduces a novel heuristic based negotiation model for urban land use planning by using multi-agent systems. The model features two kinds of agents: facilitator and advocate. Facilitator agent runs the negotiation according to a certain protocol that defines the procedure. Two roles are designated for advocate agent in the negotiation process: speaker and listener roles. Advocate agents act as a speaker on a regular basis and its role is to propose a modification of land use plan for the listener agents. The role of listener agent is to express his opinion about the proposed plan.The model also considers that the agents are socially rational in proposing and responding to the others. Social rationality is the rationality of interpersonal relations and social action; it describes that in social contexts, people do not only care about their own payoff, but also they care about others' payoff. In fact, this research also seeks to examine the link with social reasoning and use its insights to explore conflicts between individual and social concerns in an urban land use planning meeting. An illustrative example of the proposed negotiation process is performed on a real-world case study. The results of the study are presented and are compared with two other scenarios: non-collaborative scenario (purely selfish) and fully-collaborative scenario (purely altruistic). The results show that the proposed social rationality scenario is more realistic, and it has a better performance than the two other scenarios.     

Social Modeling as an Interdisciplinary Research Practice

Social modeling applies computational methods and techniques to the analysis of social processes and human behavior. It's expected to provide conceptual and technological tools for supporting analysis and decision making in areas related to national and public security, political stability, law and order, and sociocultural changes. Modeling social and cultural processes must draw on the knowledge obtained within social sciences, including conceptual models, cultural insights, and empirical data. However, how to best integrate social scientific knowledge into modeling remains an open research problem. The author presents the perspective of a social scientist to describe why modeling can be useful for social research on political violence, social conflicts, and cultural changes. She develops an interactionist approach to interdisciplinary research practice and discusses how this approach can help identify the problems related to the integration of social scientific knowledge in modeling. The discussion focuses upon research on political violence and related sociocultural processes.     

A framework for protein structure prediction on the grid

The large number of protein sequences, provided by genomic projects at an increasing pace, constitutes a challenge for large scale computational studies of protein structure and thermodynamics. Grid technology is very suitable to face this challenge, since it provides a way to access the resources needed in compute and data intensive applications. In this paper, we show the procedure to adapt to the Grid an algorithm for the prediction of protein thermodynamics, using the GridWay tool. GridWay allows the resolution of large computational experiments by reacting to events dynamically generated by both the Grid and the application. Eduardo Huedo, Ph.D.: He is a Computer Engineer (1999) and Ph.D. in Computer Architecture (2004) by the Universidad Complutense de Madrid (UCM). He is Scientist in the Advanced Computing Laboratory at Centro de Astrobiología (CSIC-INTA), associated to NASA Astrobiology Institute. He had one appointment in 2000 as a Summer Student in High Performance Computing and Applied Mathematics at ICASE (NASA Langley Research Center). His research areas are Performance Management and Tuning, High Performance Computing and Grid Technology. Ugo Bastolla, Ph.D.: He received his degree and Ph.D. in Physics in Rome University, with L. Peliti and G. Parisi respectively. He was interested from the beginning in biologically motivated problems, therefore, studied models of Population Genetics, Boolean Networks, Neural Networks, Statistical Mechanics of Polymers, Ecological and Biodiversity. His main research interest is constituted by studies of protein folding thermodynamics and evolution. Thereby, he set up an effective energy function allowing prediction of protein folding thermodynamics, and applied it to protein structure prediction, to simulate protein evolution and to analyze protein sequences from a thermodynamical point of view. He is currently in the Bioinformatic Unit of the Centro de Astrobiología of Madrid. Rubén S. Montero, Ph.D.: He received his B.S. in Physics (1996), M.S in Computer Science (1998) and Ph.D. in Computer Architecture (2002) from the Universidad Complutense de Madrid (UCM). He is Assistant Professor of Computer Architecture and Technology at UCM since 1999. He has held several research appointments at ICASE (NASA Langley Research Center), where he worked on computational fluid dynamics, parallel multigrid algorithms and Cluster computing. Nowadays, his research interests lie mainly in Grid Technology, in particular in adaptive scheduling, adaptive execution and distributed algorithms. Ignacio M. Llorente, Ph.D.: He received his B.S. in Physics (1990), M.S in Computer Science (1992) and Ph.D. in Computer Architecture (1995) from the Universidad Complutense de Madrid (UCM). He is Executive M.B.A. by Instituto de Empresa since 2003. He is Associate Professor of Computer Architecture and Technology in the Department of Computer Architecture and System Engineering at UCM and Senior Scientist at Centro de Astrobiología (CSIC-INTA), associated to NASA Astrobiology Institute. He has held several appointments since 1997 as a Consultant in High Performance Computing and Applied Mathematics at ICASE (NASA Langley Research Center). His research areas are Information Security, High Performance Computing and Grid Technology.     

A survey on sentiment analysis and opinion mining for social multimedia

Social media sentiment analysis (also known as opinion mining) which aims to extract people’s opinions, attitudes and emotions from social networks has become a research hotspot. Conventional sentiment analysis concentrates primarily on the textual content. However, multimedia sentiment analysis has begun to receive attention since visual content such as images and videos is becoming a new medium for self-expression in social networks. In order to provide a reference for the researchers in this active area, we give an overview of this topic and describe the algorithms of sentiment analysis and opinion mining for social multimedia. Having conducted a brief review on textual sentiment analysis for social media, we present a comprehensive survey of visual sentiment analysis on the basis of a thorough investigation of the existing literature. We further give a summary of existing studies on multimodal sentiment analysis which combines multiple media channels. We finally summarize the existing benchmark datasets in this area, and discuss the future research trends and potential directions for multimedia sentiment analysis. This survey covers 100 articles during 2008–2018 and categorizes existing studies according to the approaches they adopt.

     

Multi-opinion Ring: visualizing and predicting multiple opinion orientations in online social media

In the era of the Social Web, actors (e.g. people, organizations, nations, etc) of online social media often voice out their opinions towards a variety of opinion targets. Extracting and visualizing distributions of multiple opinions among actors facilitates individuals or organizations to extract valuable social intelligence from online social media. The main contribution of our research reported in this paper is the development of a novel opinion analysis methodology named Multi-opinion Ring for visualizing and predicting multiple opinion orientations held by different groups of actors in online social media. In particular, the proposed Multi-opinion Ring method combines visualization techniques with machine learning methods to predict the opinion inclinations of actors who are originally neutral to different opinion targets. A series of controlled experiments, user-based evaluations, and case studies show that the proposed Multi-opinion Ring method significantly outperforms classical visualization methods in terms of the cohesiveness of the graphical layout and the informativeness of the visualized contents.     

社会标注及其在信息检索中的应用研究综述

社会标注作为一种新型的网络资源管理和组织形式,在互联网和企业网中已经成为一种普遍的网络服务。社会标注具有标引、分类、资源发现和语义特性,这些特性可以帮助用户找到预期的信息。因此,可以利用社会标注来进行信息检索。该文首先对社会标注及标注对象和标注方法进行了概述。然后,从社会标注的分类特性、社区发现以及社会标注与语义搜索等方面进行综述评论。最后,讨论社会标注研究领域存在的挑战,并指出未来可能的研究方向。     

Investigating information sharing behavior: the mediating roles of the desire to share information in virtual communities

Social networking sites are built and designed to provide online services and a platform for people to social interacts and exchange information. This study used the social capital theory as a foundation to explore the social interaction factors and individual factors such as shared value, community identification, and information privacy concerns, and examine the mediating role of the desire to give information between trust on websites/members and information sharing behaviour in the proposed model. This research sample consists of seven hundred and twenty-seven members who have used the Facebook fan page for at least 6 months. This study adopted structural equation modeling to test the research hypotheses. The results of this study show that shared value, community identification, and information privacy concern directly influence trust on websites and members. Trust on websites and members directly influenced the desire to get/give information. Desire to give information directly influences information sharing behaviour. The desire to give information plays important mediating roles between trust on websites/members and information sharing behaviour. Finally, we provide conclusions and managerial implications of the findings.     

Control of attendance applied in higher education through mobile NFC technologies

This paper presents an improved attendance control system, required for continuous evaluation which has become compulsory following the Bologna Process. It provides a solution based on NFC technology and is based on a real project developed and pilot tested at the “Universidad Pontificia de Salamanca, Campus Madrid”.     

Critical success factors for motivating and sustaining women's ICT learning

Information Communication Technology (ICT) has changed the way people think, behave, communicate, and work. As a result, digital literacy, an essential skill for career development, lifelong learning, freedom of expression and social inclusion, is now one of the most important issues facing women today. The aim of this study was to identify the key factors and the possible mechanisms that motivate middle-aged and older females to acquire and utilize ICT skills. Drawing on Social Cognitive and Social Capital theories, we developed a theoretical model and validated it through Partial Least Squares (PLS) and mediation analyses. A survey was administered to 181 participants in an ICT learning program for digital-illiterate and middle-aged females. 133 responses were available for final analysis. The study revealed that social capital does not directly predict computer self-efficacy but depends on learning satisfaction as a mediator. In other words, unless participants develop a sense of satisfaction in class learning, a high level of social capital may not transfer into a high level of computer self-efficacy. In addition, our study shows that computer self-efficacy mediates the relationship between learning satisfaction and ICT usage, and that ICT usage and social capital both predict increases in subjective well-being. ICT utilization plays an important role in the well-being of the middle-aged and older females who often are unable to use ICT regularly due to their cultural roles. This study provides practical implications for the delivery of ICT training programs for females and other under-privileged groups.     

Social media and mental health in democracy movement in Hong Kong: A population-based study

Social media use has proliferated in the past ten years and studies are beginning to investigate the associations of social media use with political movements and mental health. This study extends this literature by testing a novel hypothesis that social resource loss on social media (e.g., “unfriending”) may be associated with increased symptoms of depression and anxiety in social upheaval. A population-based sample of 1,208 Chinese Hong Kong citizens (mean age = 46.89; 52.4% female) was recruited by random digit dialing in February 2015, two months after the conclusion of the Umbrella Movement in Hong Kong. Respondents reported social resource loss on social media, and anxiety and depressive symptoms. Hierarchical regression analyses revealed that social resource loss on social media was positively associated with depressive symptoms but not anxiety symptoms. Age moderated the positive association between social resource loss on social media and depressive symptoms. Simple slope tests revealed that the association was significant only among middle-aged (39–55 years) and older (≥56 years) adults but not younger (18–38 years) adults. The current findings shed light on the role of social media in mental health during political movements across different age groups.     

Marriage,Social Networks,and Health at Older Ages

Social relationships in older adulthood have strong connections to health and wellbeing. Connections with social network members and with spouses and long-term partners in particular, have an especially important impact on health. We highlight recent research from the National Social Life, Health, and Aging Project (NSHAP), a nationally representative, longitudinal study of aging in America, to describe the different ways health is produced in social contexts. We first discuss how social network characteristics and marital relationships influence health outcomes and sexuality, and then move on to recent findings about the ways health shapes an individual’s social world. We find that features of a social network, apart from simply its size, have strong effects on health behaviors, and that changes in network composition are associated with changes in health. We show that marriage is uniquely protective against damaging biological processes, and that the quality of a marriage influences health and well-being in nuanced ways. Finally we find that health status is associated with the ability to manage one's social network, and that health status affects the quality of one's marriage. We focus our discussion on new data from Wave 2 that enables researchers to explore how changes in social networks and partner relationships affect health and well-being during the last third of life.     

邓巴数限制下的社交网络回音室数量研究

大量研究发现，社交网络结构对观点的传播动力学特性有显著影响。提出的基于邓巴数限制的网络生成算法--DNCSN（Social Network Generation Algorithm with the Constraint of Dunbar’s Number），具有较小的平均距离和较大的群聚系数，可以生成与真实网络节点度和节点强度的非线性关系较为接近的结果。基于DNCSN生成算法，可以更为有效地研究社交网络上的观点演化特性。通过调整社交网络中个体的观点“坚定度”和观点取信阈值参数，对比研究了回音室的形成数量变化。研究表明当网络的观点初值均匀分布，网络规模小于邓巴数字时，相比于同等规模的全联通网络，DNCSN网络结构能在节点取信阈值大于0.15时减少网络的回音室的形成数量；当网络规模增大时，DNCSN网络的回音室形成数量多于全联通网络；当取信阈值小于0.1时，全联通网络的回音室形成数量受网络规模影响，且网络规模越小回音室数量越少。     

Gender differences in e-learning satisfaction

Student learning skills differ depending on gender. The importance of studying this situation in the classroom is that recommendations can be made taking gender into consideration. In e-learning, the roles of students and teachers change. In line with recent research, the question this paper raises is whether or not gender differences also exist in e-learning. The main contribution this research makes to the literature is to provide evidence on the issues male and female students consider important in their assessment of e-subjects. This study is based on a sample of 1185 students who are doing on-line courses at the Universidad de Granada in Spain. The main conclusion is that female students are more satisfied than male students with the e-learning subjects that make up the sample. Furthermore, we find that female students assign more importance to the planning of learning, as well as to being able to contact the teacher in various ways.