Profiling, Modelling and Facilitating Online Activism

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Applying classical time-series analysis techniques to online content is challenging, as web data tends to have data quality issues and is often incomplete, noisy, or poorly aligned. In this paper, we tackle the problem of predicting the evolution of a time ...

Online social media is changing the personnel recruitment process. Until now, resumes were among the most widely used tools for the screening of job applicants. The advent of inexpensive sensors combined with the success of online video platforms has enabl ...

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 ...

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 ...

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 ...

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 ...

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 ...

The concept of an ePortfolio was introduced in 1999 as an electronic learning record and further developed to overcome the limitation of learning management systems lacking persistent storage for learning artifacts. Nowadays, educational platforms have evo ...

The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. This information growth calls for recommenders that personalize the in- formation proposed to each individual user. Nevertheless, p ...

Profiling, Modelling and Facilitating Online Activism

Chat with Graph Search

Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series

Hirability in the wild: Analysis of online conversational video resumes

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

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

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

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

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

Beyond ePortfolios: Creating, Exploiting, and Archiving Activity Traces, Learning Outcomes, and Learning Analytics as Personal Shareable Online Spaces

D2P: Distance-Based Differential Privacy in Recommenders