The Users Aren't Alright: Dangerous Mental Illness Behaviors and Recommendations

09/08/2022
by   Ashlee Milton, et al.
0

In this paper, we argue that recommendation systems are in a unique position to propagate dangerous and cruel behaviors to people with mental illnesses.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/10/2018

The Recommendation System to SNS Community for Tourists by Using Altruistic Behaviors

We have already developed the recommendation system of sightseeing infor...
research
07/29/2021

Mental Age Compatibility: Quantification through the Convolution of Probability Distributions

We build on the empirical finding that a human being's mental age is nor...
research
02/25/2018

Can a Chatbot Determine My Diet?: Addressing Challenges of Chatbot Application for Meal Recommendation

Poor nutrition can lead to reduced immunity, increased susceptibility to...
research
06/25/2019

Multi-Modal Measurements of Mental Load

This position paper describes an experiment conducted to understand the ...
research
08/31/2022

Fuse: In-Situ Sensemaking Support in the Browser

People spend a significant amount of time trying to make sense of the in...
research
05/06/2021

Everyday algorithm auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviors

A growing body of literature has proposed formal approaches to audit alg...

Please sign up or login with your details

Forgot password? Click here to reset