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Related publications (27)

Referencing in YouTube Knowledge Communication Videos

Daniel Gatica-Perez

In recent years, there has been widespread concern about misinformation and hateful content on social media that are damaging societies. Being one of the most influential social media that practically serves as a newsearch engine, YouTube has accepted crit ...

Assoc Computing Machinery2023

Discovering perceived images of reused industrial heritage from user-generated photographs: Three mega-event reinforced industrial heritage transformation cases

Huishu Deng

Cities are increasingly reusing industrial heritage as part of cultural and creative regeneration strategies. However, designers and decision-makers face the challenge of determining which features and elements of industrial heritage are more perceived and ...

Springer2024

Is Your Time Well Spent Online?: Focusing on Quality Experiences Through a User-Centered Recommendation Algorithm and Simulation Model

Denis Gillet, Sandy Ingram, Rania Islambouli

Spending an uncontrolled quantity and quality of time on digital news and social media platforms can negatively influence mental health and decrease cognitive abilities. In this paper, we propose a sequential news recommendation system employing deep reinf ...

IEEE2022

HyperLogLog: Exponentially Bad in Adversarial Settings

Mathilde Aliénor Raynal

Computing the count of distinct elements in large data sets is a common task but naive approaches are memory-expensive. The HyperLogLog (HLL) algorithm (Flajolet et al., 2007) estimates a data set's cardinality while using significantly less memory than a ...

IEEE COMPUTER SOC2022

The Role of Compromised Accounts in Social Media Manipulation

Tugrulcan Elmas

In recent years we have seen a marked increase in disinformation including as part of a strategy of so-called hybrid warfare. Adversaries not only directly spread misleading content but manipulate social media by employing sophisticated techniques that exp ...

EPFL2022

DELF: Safeguarding deletion correctness in Online Social Networks

Georgios Damaskinos

Deletion is a core facet of Online Social Networks (OSNs). For users, deletion is a tool to remove what they have shared and control their data. For OSNs, robust deletion is both an obligation to their users and a risk when developer mistakes inevitably oc ...

USENIX ASSOC2020

The (Co)-Location Sharing Game

Jean-Pierre Hubaux, Kévin Clément Huguenin, Mathias Jacques Jean-Marc Humbert, Alexandra-Mihaela Olteanu

Most popular location-based social networks, such as Facebook and Foursquare, let their (mobile) users post location and co-location (involving other users) information. Such posts bring social benefits to the users who post them but also to their friends ...

2019

Investigating users' eye movement behavior in critiquing-based recommender systems

Pearl Pu Faltings, Li Chen

Recommender systems have increasingly become popular in various web environments (such as e-commerce and social media) for automatically generating items that match to individual users' personal interests. Among different types of recommender systems that ...

Ios Press2017

Profiling, Modelling and Facilitating Online Activism

Julia Proskurnia

The extensive and successful use of social media has enhanced and empowered a variety of movements all over the world in a way that is hard to achieve through conventional means. This has led to numerous studies that leverage online social data to describe ...

EPFL2017

Enhancing Social Media Platforms for Educational and Humanitarian Knowledge Sharing : Analytics, Privacy, Discovery, and Delivery Aspects

Andrii Vozniuk

Social media (SM) platforms have demonstrated their ability to facilitate knowledge sharing on the global scale. They are increasingly often employed in educational and humanitarian domains where, despite their general benefits, they expose challenges pecu ...

EPFL2017

Context-Dependent Privacy-Aware Photo Sharing based on Machine Learning

Touradj Ebrahimi, Lin Yuan, Joël Régis Theytaz

Photo privacy has raised a growing concern with the advancements of image analytics, face recognition, and deep learning techniques widely applied on social media. If properly deployed, these powerful techniques can in turn assist people in enhancing their ...

2017

Learning Explainable User Sentiment and Preferences for Information Filtering

Nikolaos Pappas

In the last decade, online social networks have enabled people to interact in many ways with each other and with content. The digital traces of such actions reveal people's preferences towards online content such as news or products. These traces often res ...

EPFL2016

Context and Semantic Aware Location Privacy

Berker Agir

With ever-increasing computational power, and improved sensing and communication capabilities, smart devices have altered and enhanced the way we process, perceive and interact with information. Personal and contextual data is tracked and stored extensivel ...

EPFL2016

Rule of Thumb – Effect of Social Button Icons on Interaction

Denis Gillet, Adrian Christian Holzer, Andrii Vozniuk, Samuel Bendahan

Social buttons are now widespread in social media apps. They are used to assign weight to user content and trigger user engagement. They come in different shapes (e.g., thumb in Facebook, arrows in Reddit or StackOverflow, plus one in Google+) but very lit ...

2016

A Machine-Learning Based Approach to Privacy-Aware Information-Sharing in Mobile Social Networks

Jean-Pierre Hubaux, Murtuza Jadliwala, Kévin Clément Huguenin, Igor Bilogrevic, Berker Agir, Maria Gazaki

Contextual information about users is increasingly shared on mobile social networks. Examples of such information include users' locations, events, activities, and the co-presence of others in proximity. When disclosing personal information, users take int ...

Elsevier Science Bv2016

Personalizing Product Rankings Using Collaborative Filtering on Opinion-Derived Topic Profiles

Boi Faltings, Claudiu-Cristian Musat

Product review sites such as TripAdvisor, Yelp or Amazon provide a single, non personalized ranking of products. The sparse review data makes personalizing recommendations difficult. Topic Profile Collaborative Filtering exploits review texts to identify u ...

2015

Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms

Jean-Pierre Hubaux, Reza Shokri, Kévin Clément Huguenin, Igor Bilogrevic

Location check-ins contain both geographical and semantic information about the visited venues, in the form of tags (e.g., “restaurant”). Such data might reveal some personal information about users beyond what they actually want to disclose, hence their p ...

2015

Social Interface and Interaction Design for Group Recommender Systems

Yu Chen

Group recommender systems suggest items of interest to a group of people. Traditionally, group recommenders provide recommendations by aggregation the group membersâ preferences. Nowadays, there is a trend of decentralized group recommendation process th ...

EPFL2015

Semantic-Improved Color Imaging Applications: It Is All About Context

Sabine Süsstrunk, Albrecht Johannes Lindner

Multimedia data with associated semantics is omnipresent in today’s social online platforms in the form of keywords, user comments and so forth. This article presents a statistical framework designed to infer knowledge in the imaging domain from the semant ...

2015

Comparing the Predictive Capability of Social and Interest Affinity for Recommendations

Karl Aberer, Anne-Marie Kermarrec, Alexandra Olteanu

The advent of online social networks created new prediction opportunities for recommender systems: instead of relying on past rating history through the use of collaborative filtering (CF), they can leverage the social relations among users as a predictor ...

Springer-Verlag Berlin2014