Peeking into the other half of the glass : handling polarization in recommender systems.

This dissertation is about filtering and discovering information online while using recommender systems. In the first part of our research, we study the phenomenon of polarization and its impact on filtering and discovering information. Polarization is a social phenomenon, with serious consequences, in real-life, particularly on social media. Thus it is important to understand how machine learning algorithms, especially recommender systems, behave in polarized environments. We study polarization within the context of the users\u27 interactions with a space of items and how this affects recommender systems. We first formalize the concept of polarization based on item ratings and then relate it to the item reviews, when available. We then propose a domain independent data science pipeline to automatically detect polarization using the ratings rather than the properties, typically used to detect polarization, such as item\u27s content or social network topology. We perform an extensive comparison of polarization measures on several benchmark data sets and show that our polarization detection framework can detect different degrees of polarization and outperforms existing measures in capturing an intuitive notion of polarization. We also investigate and uncover certain peculiar patterns that are characteristic of environments where polarization emerges: A machine learning algorithm finds it easier to learn discriminating models in polarized environments: The models will quickly learn to keep each user in the safety of their preferred viewpoint, essentially, giving rise to filter bubbles and making them easier to learn. After quantifying the extent of polarization in current recommender system benchmark data, we propose new counter-polarization approaches for existing collaborative filtering recommender systems, focusing particularly on the state of the art models based on Matrix Factorization. Our work represents an essential step toward the new research area concerned with quantifying, detecting and counteracting polarization in human-generated data and machine learning algorithms.We also make a theoretical analysis of how polarization affects learning latent factor models, and how counter-polarization affects these models. In the second part of our dissertation, we investigate the problem of discovering related information by recommendation of tags on social media micro-blogging platforms. Real-time micro-blogging services such as Twitter have recently witnessed exponential growth, with millions of active web users who generate billions of micro-posts to share information, opinions and personal viewpoints, daily. However, these posts are inherently noisy and unstructured because they could be in any format, hence making them difficult to organize for the purpose of retrieval of relevant information. One way to solve this problem is using hashtags, which are quickly becoming the standard approach for annotation of various information on social media, such that varied posts about the same or related topic are annotated with the same hashtag. However hashtags are not used in a consistent manner and most importantly, are completely optional to use. This makes them unreliable as the sole mechanism for searching for relevant information. We investigate mechanisms for consolidating the hashtag space using recommender systems. Our methods are general enough that they can be used for hashtag annotation in various social media services such as twitter, as well as for general item recommendations on systems that rely on implicit user interest data such as e-learning and news sites, or explicit user ratings, such as e-commerce and online entertainment sites. To conclude, we propose a methodology to extract stories based on two types of hashtag co-occurrence graphs. Our research in hashtag recommendation was able to exploit the textual content that is available as part of user messages or posts, and thus resulted in hybrid recommendation strategies. Using content within this context can bridge polarization boundaries. However, when content is not available, is missing, or is unreliable, as in the case of platforms that are rich in multimedia and multilingual posts, the content option becomes less powerful and pure collaborative filtering regains its important role, along with the challenges of polarization

CHORUS Deliverable 3.4: Vision Document

The goal of the CHORUS Vision Document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area and to highlight trends and challenges in this domain. The vision of CHORUS is strongly connected to the CHORUS Roadmap Document (D2.3). A concise document integrating the outcomes of the two deliverables will be prepared for the end of the project (NEM Summit)

Selection Bias in News Coverage: Learning it, Fighting it

News entities must select and filter the coverage they broadcast through their respective channels since the set of world events is too large to be treated exhaustively. The subjective nature of this filtering induces biases due to, among other things, resource constraints, editorial guidelines, ideological affinities, or even the fragmented nature of the information at a journalist's disposal. The magnitude and direction of these biases are, however, widely unknown. The absence of ground truth, the sheer size of the event space, or the lack of an exhaustive set of absolute features to measure make it difficult to observe the bias directly, to characterize the leaning's nature and to factor it out to ensure a neutral coverage of the news. In this work, we introduce a methodology to capture the latent structure of media's decision process on a large scale. Our contribution is multi-fold. First, we show media coverage to be predictable using personalization techniques, and evaluate our approach on a large set of events collected from the GDELT database. We then show that a personalized and parametrized approach not only exhibits higher accuracy in coverage prediction, but also provides an interpretable representation of the selection bias. Last, we propose a method able to select a set of sources by leveraging the latent representation. These selected sources provide a more diverse and egalitarian coverage, all while retaining the most actively covered events

Next Generation Metrics for Scientific and Scholarly Research in Europe:LERU report of an Expert Working Group

The field of evaluating academic activities is vast, complex, and highly dynamic, as are the roles of any data and indicators used to support these evaluations This Next Generation Metrics for Scientific and Scholarly Research in Europe paper, explores how universities can and should use currently available metrics and data to assess their research evaluation processes, in conjunction with qualitative expertise and information

Towards solutions for assistive technology

Introduction What is assistive technology? The agreed World Health Organisation definition is "Assistive technology can be defined as “any piece of equipment, or product, whether it is acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities” (WHO, 2011) The array of possible assistive technology products and solutions reflects the diversity of the needs of people with disabilities – ranging from digital technologies that can support social engagement, communication, employment, learning, memory, planning and safe guarding services through to products and devices that support mobility and personal care requirements. Typically as the complexities of assistive technology solutions increase, so do the costs and potential risks (if not appropriately set up or maintained). This document is primarily focused on the Assistive Technology solutions derived from aids and equipment. Home and vehicle modifications and prosthetics have not yet been explored in the same level of detail and will be subject of further work. Proposed approach The proposed assistive technology service approach has been developed in line with the strategic goals of the NDIA. It is one aspect of a broader strategic approach the NDIA has to using technologies to enhance its engagement and management of relationships, services and supports with suppliers, providers, participants and the Australian community. The NDIA’s goal is to use technology in its various forms to ensure that services, supports, and communications between all stakeholders are as streamlined as possible and services are timely and effective. This document outlines the elements of a proposed service delivery approach for individuals to access assistive technology solutions and is based on the three key objectives outlined above

The Effects of Social Media in the Hotel Sector: A report for WinHotels

Social media usage is expanding in all age groups and across all socio-economic groups. This means it has become the focus of much attention from businesses looking to use it as a way to increase awareness of their products or services. The purpose of this report is to look at how social media is affecting the hotel business and whether Win Hotels should be using social media as a marketing tool. It offers the opportunity to engage with hotel guests before during and after a stay. This engagement provides the hotel with a chance to gain insights into the needs and wants of guests at each stage. Using this information to highlight where improvements could be made to offer better service and showcase the hotel’s willingness to listen and respond to guests. The advantages of using social media are clear: it has the potential to reach large audiences and could generate large amounts of traffic to the WinHotels website. The downsides of a mishandled campaign are the speed and ease with which damage to a brand can happen. This report looks at how social media could benefit WinHotels and where it could fit into its marketing activities. It will also suggest steps that should be taken in order to set expectations and provide recommendations on how to model a campaign incorporating the use of social media

Towards the development of a resource allocation model for primary, continuing and community care in the health services - Volume 1

This report proposes a resource allocation model for the Irish health services based on the principle that each Irish resident should be provided with access to health services funded from general taxation and in proportion to their need for those services. At the moment, such a system cannot be deployed as some necessary financial information is not available. The information could be made available, and should be done as quickly as possible. If this information were made available, the model proposed here, while very crude, would serve as a good starting point for resource allocation and should be initiated as soon as possible. Any reasonable system of resource allocation would be an improvement on the system that is currently in place

The metric tide: report of the independent review of the role of metrics in research assessment and management

This report presents the findings and recommendations of the Independent Review of the Role of Metrics in Research Assessment and Management. The review was chaired by Professor James Wilsdon, supported by an independent and multidisciplinary group of experts in scientometrics, research funding, research policy, publishing, university management and administration. This review has gone beyond earlier studies to take a deeper look at potential uses and limitations of research metrics and indicators. It has explored the use of metrics across different disciplines, and assessed their potential contribution to the development of research excellence and impact. It has analysed their role in processes of research assessment, including the next cycle of the Research Excellence Framework (REF). It has considered the changing ways in which universities are using quantitative indicators in their management systems, and the growing power of league tables and rankings. And it has considered the negative or unintended effects of metrics on various aspects of research culture. The report starts by tracing the history of metrics in research management and assessment, in the UK and internationally. It looks at the applicability of metrics within different research cultures, compares the peer review system with metric-based alternatives, and considers what balance might be struck between the two. It charts the development of research management systems within institutions, and examines the effects of the growing use of quantitative indicators on different aspects of research culture, including performance management, equality, diversity, interdisciplinarity, and the ‘gaming’ of assessment systems. The review looks at how different funders are using quantitative indicators, and considers their potential role in research and innovation policy. Finally, it examines the role that metrics played in REF2014, and outlines scenarios for their contribution to future exercises

Built to last! Embedding open science principles and practice into European universities

The purpose of this article is to examine the cultural change needed by universities, as identified by LERU in its report Open Science and its role in universities: a roadmap for cultural change.1 It begins by illustrating the nature of that cultural change. Linked to that transformation is a necessary management change to the way in which organizations perform research. Competition is not the only, or necessarily the best, way to conduct this transformation. Open science brings to the fore the values of collaboration and sharing. Building on a number of Focus on Open Science Workshops held over five years across Europe, the article identifies best practice in changing current research practices, which will then contribute to the culture change necessary to deliver open science. Four case studies, delivered at Focus on Open Science Workshops or other conferences in Europe, illustrate the advances that are being made: the findings of a Workshop on Collaboration and Competition at the OAI 11 meeting in Geneva in June 2019; alternative publishing platforms, exemplified by UCL Press; open data, FAIR data and reproducibility; and a Citizen Science Workshop held at the LIBER Conference in Dublin in June 2019

Building the Science Foundation of a Modern Food Safety System: Lessons From Denmark, the Netherlands, and the United Kingdom on Creating a More Coordinated and Integrated Approach to Food Safety Information

Examines how food safety reforms in three countries and the European Union affected data collection and analysis, coordination and integrated approaches, and use of data for prevention. Makes recommendations for U.S. programs, policies, and activities