Who is the" human" in human-centered machine learning: The case of predicting mental health from social media
S Chancellor, EPS Baumer… - Proceedings of the ACM …, 2019 - dl.acm.org
" Human-centered machine learning"(HCML) combines human insights and domain
expertise with data-driven predictions to answer societal questions. This area's inherent …
expertise with data-driven predictions to answer societal questions. This area's inherent …
Quantifying mental health from social media with neural user embeddings
Mental illnesses adversely affect a significant proportion of the population worldwide.
However, the typical methods to estimate and characterize the prevalence of mental health …
However, the typical methods to estimate and characterize the prevalence of mental health …
Machine learning in mental health: A systematic review of the HCI literature to support the development of effective and implementable ML systems
High prevalence of mental illness and the need for effective mental health care, combined
with recent advances in AI, has led to an increase in explorations of how the field of machine …
with recent advances in AI, has led to an increase in explorations of how the field of machine …
Toward practices for human-centered machine learning
S Chancellor - Communications of the ACM, 2023 - dl.acm.org
Toward Practices for Human-Centered Machine Learning Page 1 MACHINE LEARNING (ML)
has been described as a modern Oracle of Delphi—a way to quickly solve problems in different …
has been described as a modern Oracle of Delphi—a way to quickly solve problems in different …
[HTML][HTML] Predicting future mental illness from social media: A big-data approach
R Thorstad, P Wolff - Behavior research methods, 2019 - Springer
In the present research, we investigated whether people's everyday language contains
sufficient signal to predict the future occurrence of mental illness. Language samples were …
sufficient signal to predict the future occurrence of mental illness. Language samples were …
Methodological gaps in predicting mental health states from social media: Triangulating diagnostic signals
A growing body of research is combining social media data with machine learning to predict
mental health states of individuals. An implication of this research lies in informing evidence …
mental health states of individuals. An implication of this research lies in informing evidence …
A taxonomy of ethical tensions in inferring mental health states from social media
S Chancellor, ML Birnbaum, ED Caine… - Proceedings of the …, 2019 - dl.acm.org
Powered by machine learning techniques, social media provides an unobtrusive lens into
individual behaviors, emotions, and psychological states. Recent research has successfully …
individual behaviors, emotions, and psychological states. Recent research has successfully …
Gender and cross-cultural differences in social media disclosures of mental illness
M De Choudhury, SS Sharma, T Logar… - Proceedings of the …, 2017 - dl.acm.org
Cultural and gender norms shape how mental illness and therapy are perceived. However,
there is a paucity of adequate empirical evidence around gender and cultural dimensions of …
there is a paucity of adequate empirical evidence around gender and cultural dimensions of …
A computational study of mental health awareness campaigns on social media
As public discourse continues to progress online, it is important for mental health advocates,
public health officials, and other curious parties and stakeholders, ranging from researchers …
public health officials, and other curious parties and stakeholders, ranging from researchers …
Trending: The promises and the challenges of big social data
L Manovich - Debates in the digital humanities, 2011 - books.google.com
LEV MANOVICH oday, the term “big data” is often used in popular media, business,
computer science, and the computer industry. For instance, in June 2008, Wired maga-zine …
computer science, and the computer industry. For instance, in June 2008, Wired maga-zine …