Implicit feedback-based group recommender system for internet of things applications

With the prevalence of Internet of Things (IoT)-based social media applications, the distance among people has been greatly shortened. As a result, recommender systems in IoT-based social media need to be developed oriented to groups of users rather than individual users. However, existing methods were highly dependent on explicit preference feedbacks, ignoring scenarios of implicit feedbacks. To remedy such gap, this paper proposes an implicit feedback-based group recommender system using probabilistic inference and non-cooperative game (GREPING) for IoT-based social media. Particularly, unknown process variables can be estimated from observable implicit feedbacks via Bayesian posterior probability inference. In addition, the globally optimal recommendation results can be calculated with the aid of non-cooperative game. Two groups of experiments are conducted to assess the GREPING from two aspects: efficiency and robustness. Experimental results show obvious promotion and considerable stability of the GREPING compared to baseline methods. © 2020 IEEE

Instagram Stories versus Facebook Wall: an advertising effectiveness analysis

Purpose – This paper aims to investigate advertising effectiveness in Instagram and Facebook, the two most important social media platforms. It helps to understand which should be chosen depending on the target audience of the campaign. Design/methodology/approach – The study examines advertising effectiveness in these social media in terms of ad attitude, ad intrusiveness and loyalty intentions. An online survey was conducted with 303 social media users. Age and gender are proposed as moderators. Findings – The results indicate that Instagram Stories not only enhances consumer attitude toward ads but also increases perceived intrusiveness, compared to Facebook Wall. Millennials are more disturbed by Facebook Wall ads than non-millennial users. A triple interaction effect reveals that non-millennial men are more loyal toward Facebook Wall ads, whereas millennials of both genders and non-millennial women are more loyal to ads on Instagram Stories. Practical implications – Advertisers should be aware of the differential features and segmentation possibilities in social media to better address their target audiences. More precisely, the research findings suggest that professionals should focus on Instagram Stories when targeting millennials and non-millennial women, and on Facebook Wall when targeting non-millennial men. Originality/value – This study is one of the first to contribute to the literature on Instagram Stories as an advertising platform and compare its differential features with those of more established social media, such as Facebook Wall. Proposito de la investigacion – Esta investigacion compara la efectividad publicitaria en Instagram yFacebook en funcion del público objetivo. Metodología y diseño – La investigacion analiza las diferencias entre cada formato de red social en términosde actitud hacia el anuncio, intrusividad percibida y lealtad hacia el producto o marca anunciado. Mediante unaencuesta online a 303 consumidores, se proponen efectos directos y efectos moderacion de la edad y el género. Recomendaciones – Los resultados indican que Instagram Stories mejora la actitud hacía el anuncio, peroaumenta también la intrusividad en comparacion con Facebook Wall. La publicidad en Facebook Wall es másintrusiva para los millennials que para los no-millennials. Instagram Stories incrementa la lealtad entre losusuarios millennial de ambos sexos y las mujeres no-millennial; en cambio, los hombres no-millennial son másleales a la publicidad en Facebook Wall. Implicaciones prácticas – Los anunciantes deben aprovechar los nuevos formatos y las posibilidades desegmentacion que les brindan las redes sociales para llegar a su público objetivo de manera más efectiva. Concretamente, los hallazgos de la investigacion sugieren que deberían centrarse en Instagram Stories paradirigirse a un público millennial y a mujeres no-millennial; y en Facebook Wall, cuando su público objetivosean los hombres no-millennial. Originalidad – Este estudio es uno de los primeros que aborda el uso de Instagram Stories como soportepublicitario y lo compara con formatos publicitarios consolidados como Facebook Wal

XRay: Enhancing the Web's Transparency with Differential Correlation

Today's Web services - such as Google, Amazon, and Facebook - leverage user data for varied purposes, including personalizing recommendations, targeting advertisements, and adjusting prices. At present, users have little insight into how their data is being used. Hence, they cannot make informed choices about the services they choose. To increase transparency, we developed XRay, the first fine-grained, robust, and scalable personal data tracking system for the Web. XRay predicts which data in an arbitrary Web account (such as emails, searches, or viewed products) is being used to target which outputs (such as ads, recommended products, or prices). XRay's core functions are service agnostic and easy to instantiate for new services, and they can track data within and across services. To make predictions independent of the audited service, XRay relies on the following insight: by comparing outputs from different accounts with similar, but not identical, subsets of data, one can pinpoint targeting through correlation. We show both theoretically, and through experiments on Gmail, Amazon, and YouTube, that XRay achieves high precision and recall by correlating data from a surprisingly small number of extra accounts.Comment: Extended version of a paper presented at the 23rd USENIX Security Symposium (USENIX Security 14

A Bayesian social platform for inclusive and evidence-based decision making

Against the backdrop of a social media reckoning, this paper seeks to demonstrate the potential of social tools to build virtuous behaviours online. We must assume that human behaviour is flawed, the truth can be elusive, and as communities we must commit to mechanisms to encourage virtuous social digital behaviours. Societies that use social platforms should be inclusive, responsive to evidence, limit punitive actions and allow productive discord and respectful disagreement. Social media success, we argue, is in the hypothesis. Documents are valuable to the degree that they are evidence in service of, or to challenge an idea for a purpose. We outline how a Bayesian social platform can facilitate virtuous behaviours to build evidence-based collective rationality. The chapter outlines the epistemic architecture of the platform's algorithms and user interface in conjunction with explicit community management to ensure psychological safety. The BetterBeliefs platform rewards users who demonstrate epistemically virtuous behaviours and exports evidence-based propositions for decision-making. A Bayesian social network can make virtuous ideas powerful.Comment: 38 pages, 3 tables, 13 figures submitted for peer review for inclusion in M. Alfano, C. Klein and J de Ridder (Eds.) Social Virtue Epistemology. Routledge [forthcoming