Social networks and news outlets use recommender systems to distribute information and suggest news to their users. These algorithms are an attractive solution to deal with the massive amount of content on the web [6]. However, some organisations prioritise retention and maximisation of the number of access, which can be incompatible with values like the diversity of content and transparency. In recent years critics have warned of the dangers of algorithmic curation. The term filter bubbles, coined by the internet activist Eli Pariser [1], describes the outcome of pre-selected personalisation, where users are trapped in a bubble of similar contents. Pariser warns that it is not the user but the algorithm that curates and selects interesting topics to watch or read. Still, there is disagreement about the consequences for individuals and society. Research on the existence of filter bubbles is inconclusive. Fletcher in [5], claims that the term filter bubbles is an oversimplification of a much more complex system involving cognitive processes and social and technological interactions. And most of the empirical studies indicate that algorithmic recommendations have not locked large segments of the audience into bubbles [3] [6]. We built an agent-based simulation tool to study the dynamic and complex interplay between individual choices and social and technological interaction. The model includes different recommendation algorithms and a range of cognitive filters that can simulate different social network dynamics. The cognitive filters are based on the triple-filter bubble model [2]. The tool can be used to understand under which circumstances algorithmic filtering and social network dynamics affect users' innate opinions and which interventions on recommender systems can mitigate adverse side effects like the presence of filter bubbles. The resulting tool is an open-source interactive web interface, allowing the simulation with different parameters such as users' characteristics, social networks and recommender system settings (see Fig. 1). The ABM model, implemented in Python Mesa [4], allows users to visualise, compare and analyse the consequence of combining various factors. Experiment results are similar to the ones published in the Triple Filter Bubble paper [2]. The novelty is the option to use a real collaborative-filter recommendation system and a new metric to measure the distance between users' innate and final opinions. We observed that slight modifications in the recommendation system, exposing items within the boundaries of users' latitude of acceptance, could increase content diversity.References 1. Pariser, E.: The filter bubble: What the internet is hiding from you. Penguin, New York, NY (2011) 2. Geschke, D., Lorenz, J., Holtz, P.: The triple-filter bubble: Using agent-based modelling to test a meta-theoretical framework for the emergence of filter bubbles and echo chambers. British Journal of Social Psychology (2019), 58, 129–149 3. Möller, J., Trilling, D., Helberger, N. , and van Es, B.: Do Not Blame It on the Algorithm: An Empirical Assessment of Multiple Recommender Systems and Their Impact on Content Diversity. Information, Communication and Society 21, no. 7 (2018): 959–77 4. Mesa: Agent-based modeling in Python, https://mesa.readthedocs.io/. Last accessed 2 Sep 2022 5. Fletcher, R.: The truth behind filter bubbles: Bursting some myths. Digital News Report - Reuters Institute (2020). https://reutersinstitute.politics.ox.ac.uk/news/truth-behind-filter-bubblesbursting-some-myths. Last accessed 2 Sep 2022 6. Haim, M., Graefe, A, Brosius, H: Burst of the Filter Bubble?: Effects of Personalization on the Diversity of Google News. Digital Journalism 6, no. 3 (2018): 330–43.
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06-11-2022
Given the growing number of older people, society as a whole should ideally provide a higher quality of life (QoL) for its ageing citizens through the concept of personalised ageing. Information and communication technologies (ICT) are subject to constant and rapid development, and can contribute to the goal of an improved QoL for older adults. In order to utilise future ICT solutions as a part of an age-friendly smart environment that helps achieve personalised ageing with an increased QoL, one must first determine whether the existing ICT solutions are satisfying the needs of older people. In order to accomplish that, this study contributes in three ways. First, it proposes a framework for the QoL of older adults, in order to provide a systematic review of the state-of-the-art literature and patents in this field. The second contribution is the finding that selected ICT solutions covered by articles and patents are intended for older adults and are validated by them. The third contribution of the study are the six recommendations that are derived from the review of the literature and the patents which would help move the agenda concerning the QoL of older people and personalised ageing with the use of ICT solutions forward. Original article at MDPI; DOI: http://dx.doi.org/10.3390/ijerph17082940 (This article belongs to the Special Issue Feature Papers "Age-Friendly Cities & Communities: State of the Art and Future Perspectives")
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23-04-2020
Increasing students’ motivation in higher education by designing a specific curriculum has always been a challenging but very complex process. The Department of Business, Finance and Marketing (BFM) of The Hague University of Applied Sciences (THUAS) initiated a redesign of the curricula with the major goals of increasing flexibility of learning opportunities and offering students a more motivating, inspiring and richer diversity of learning experiences. In the literature of learning in higher education this has often been labeled as ‘offering extracurricular learning opportunities’. The redesign of the curriculum implies that the new one will result in an enhancement of the flexibility of the curriculum, by offering learning opportunities beyond the borders of specific programs like marketing, finance or entrepreneurship and retail management. The richness and diversity should create flexible platforms, offering students the possibility to enrich their career choices to design their own personalised career path, hopefully maximizing the possibilities for their talent development. However, very little is known about the relationship between the students’ satisfaction with extracurricular learning opportunities, aiming at the personalisation of students’ career choices, and their motivation. In this chapter we describe our research into this relationship between student motivation and learning environments. Designing a network curriculum by increasing the possibility of extracurricular learning opportunities in higher education could have a positive impact on students’ motivation when it is combined with activities to increase goal students’ commitment. This depends on teachers’ qualities to communicate the valence and instrumentality of the learning possibilities offered for the prospective work environment. This is a complex issue however. Teachers from different educational programs, even in the same domain, have a different orientation on existing learning opportunities within one specific program. Excellent coaching skills by tutors are important. These coaching skills are necessary to support students in the process of envisioning extracurricular learning opportunities when important career choices have to be made.
Creating and testing a Virtual Reality Therapy Application to reduce alcohol addiction. Develop and test a Virtual Reality application to be used in therapy, within Novadic Kentron, that helps people deal with alcohol addiction. By recreating real contexts in VR that either stimulate craving or elicit positive feelings, the VR application should increase, for example, self-confidence to deal with these situations and reduce relapse risks. In addition, together with students from BUas and other universities, we study the effects of different forms of realism and resemblance within virtual reality worlds. We are testing, among other things, differences between CGI-created and 360-recorded worlds that differ in level of personalisation.Partner:Novadic-Kentron
