activity
20172021
most citedFaceLift: A transparent deep learning framework to beautify urban scenes

40 citations · 48 across the 5 of their papers we have counts for

collaborators

11 papers

cs.CY2021

The Healthy States of America: Creating a Health Taxonomy with Social Media

Sanja Scepanovic, Luca Maria Aiello, Ke Zhou +2

Since the uptake of social media, researchers have mined online discussions to track the outbreak and evolution of specific diseases or chronic conditions such as influenza or depr…

cs.CV20214 cited

Jane Jacobs in the Sky: Predicting Urban Vitality with Open Satellite Data

Sanja Šćepanović, Sagar Joglekar, Stephen Law +1

The presence of people in an urban area throughout the day -- often called 'urban vitality' -- is one of the qualities world-class cities aspire to the most, yet it is one of the h…

cs.HC2020

Humane Visual AI: Telling the Stories Behind a Medical Condition

Wonyoung So, Edyta P. Bogucka, Sanja Šćepanović +3

A biological understanding is key for managing medical conditions, yet psychological and social aspects matter too. The main problem is that these two aspects are hard to quantify…

cs.SI2020

Analysing Meso and Macro conversation structures in an online suicide support forum

Sagar Joglekar, Sumithra Velupillai, Rina Dutta +1

Platforms like Reddit and Twitter offer internet users an opportunity to talk about diverse issues, including those pertaining to physical and mental health. Some of these forums a…

cs.SI2020

Characterising User Content on a Multi-lingual Social Network

Pushkal Agarwal, Kiran Garimella, Sagar Joglekar +2

Social media has been on the vanguard of political information diffusion in the 21st century. Most studies that look into disinformation, political influence and fake-news focus on…

cs.CY2020

Stop Tracking Me Bro! Differential Tracking Of User Demographics On Hyper-partisan Websites

Pushkal Agarwal, Sagar Joglekar, Panagiotis Papadopoulos +2

Websites with hyper-partisan, left or right-leaning focus offer content that is typically biased towards the expectations of their target audience. Such content often polarizes use…