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The dissemination of medical misinformation online presents a challenge to human health. Machine learning techniques provide a unique opportunity for decreasing the cognitive load associated with deciding upon whether any given user comment is likely to contain misinformation, but a paucity of labeled data of medical misinformation makes supervised approaches a challenge. In order to ameliorate this...
The number of elderly people in the world is growing rapidly. For this reason, is necessary more tools for the care, entertainment, and interaction of the elderly. This paper presents an application to foment social interaction among elderly people. This app is part of the SAFER platform, focused on meeting the needs of this part of population. The app stores in a database the profiles of the elderly...
The advent of social media in education has the potential to foster collaborative learning. Exploring students' interactions on the social media tools is an important research direction, which could bring an insight into the collaborative learning process. Therefore, our aim is to propose a conceptual framework for knowledge extraction and visualization from a social media-based learning environment...
The platform we're proposing will be the main actor of the upcoming paradigm shift from representative governance to self governance, the architecture, functionality and interface of the platform was modelled after the human anatomy. Human decision making efficiency is dependent upon the governance system of the deciding agents and the roles they play. Aligning the context in which a decision impacting...
The paper aims to identify the elements that make possible the appearance of emergent properties in organizations structured as social networks, considered as adaptive multi-agent complex systems. The dynamics of these communities (referring primarily to the increasing number of members who interact) was analyzed by the specific rules of scale-free networks growth and the specific principles of multi-agent...
Teachers today spend a lot of time grading students' work. Yet many times students feel under-appreciated and they lack understanding of the grading criteria, which leads to no improvement of their learning through time. This paper presents a perspective on automatic evaluations of students' work with the use of gamified peer assessment. Using peer assessment, students not only learn what was correct...
In the present work, we study the advertising competition of several marketing campaigns who need to determine how many resources to allocate to potential customers to advertise their products through direct marketing while taking into account that competing marketing campaigns are trying to do the same. Potential customers rank marketing campaigns according to the offers, promotions or discounts...
This PhD aims to contribute to the body of knowledge on online participation, addressing in particular the online behaviors known as lurking. Lurking is probably the most common online behavior, so it is important to understand what lurking is, how it is defined, its value and impact. A literature review shows the many definitions of lurking, and that the definition chosen impacts how online research...
In this paper, we propose and describe a novel recommender system for big data applications that provides recommendations on the base of the interactions among users and generated multimedia contents in one or more social media networks, leveraging a collaborative and user-centered approach. Preliminary experiments using data of several online social networks show how our approach obtains very promising...
In order to understand information transmission, it is highly important to find a hidden structure of a social network such as rumors in daily life, and leaders of the underground organizations. The information above is difficult to be forecasted because such information can only be obtained in fragments and cannot be achieved through observation itself based on the data. This research aims to clarify...
Communities serve as basic structures for understanding the organization of many real-world networks, such as social, biological, collaboration, and communication networks. Recently, community search over large graphs has attracted significantly increasing attention, from simple and static graphs to evolving, attributed, location-based graphs. Different from the well-studied problem of community detection...
The problem of node classification has been widely studied in a variety of network-based scenarios. In this paper, we will study the more challenging scenario in which some of the edges in a content-based network are labeled, and it is desirable to use this information in order to determine the labels of other arbitrary edges. Furthermore, each edge is associated with text content, which may correspond...
As a novel concept, "Informed Design" is being practiced in the Future Cities Laboratory at the Singapore-ETH Centre to innovate place design from empirical to evidential by harnessing geo-referenced "Big Data" for a responsive design. Initially, potentials of people sensing data derived from multi-sources, such as social networks, dedicated applications, sensors, etc., shall be...
The article describes computational experiment and further research work in the area of identification of destructive information influence in social networks. The problem of distribution of suicidal content via open sources is presented. On the basis of calculations there was made a conclusions about the prospects of using the methods of information retrieval in the task of identification of the...
Paper presents the Shape Movement Pattern (ShaMP) algorithm, an algorithm for extracting Movement Patterns (MPs) from network data, and a prediction mechanism whereby the identified MPs can be used to predict the nature of movement in a previously unseen network. The principal advantage offered by ShaMP is that it lends itself to parallelisation. The reported evaluation was conducted using both Massage...
If many are still skeptical about the contribution of virtual environments in the learning process, others are still debating on the significant differences between traditional and online education. In other words, information and communication technologies are yet to be viewed as the indispensable pedagogical and learning tool, enabling meta-cognitive development and autonomous learning. Virtual...
Absence of the user based recommendation system is a prevalent problem in a social network. In this paper, our work tends to model distance based group and probability based group in terms deciding recommendation dynamics. Here, we want to identify the best user who appears to be the innocent audience. In this regard, the effect of network density and preference homogeneity according to the user have...
This paper proposes CPERS, a contextual and personalized event recommender system that exploits overall user preference and context influences to produce recommendations in event-based social networks (EBSNs). Diversely from items in traditional recommendation scenarios (e.g. movies, songs), events in EBSNs are only valid for a short period of time, having no explicit feedback. Therefore the event...
Link prediction is a “hot topic” in network analysis and has been largely used for friendship recommendation in social networks. With the increased use of location-based services, it is possible to improve the accuracy of link prediction methods by using the mobility of users. The majority of the link prediction methods focus on the importance of location for their visitors, disregarding the strength...
Big Data technology is a generic technology, which can be applied to any real-world problem that involves a lot of data. Moreover, the use of cloud-based infrastructure to implement the big data technology makes it a cost-effective solution to the big data problem. One of the fundamental sectors that can benefit from this technology is education and research. The education system can use big data...
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