Social media provide access to behavioural data at an unprecedented scale and granularity.
However, using these data to understand phenomena in a broader population is difficult due …

Many significant challenges exist for the mental health field, but one in particular is a lack of
data available to guide research. Language provides a natural lens for studying mental …

In the United States, the country with the highest confirmed COVID-19 infection cases, a
nationwide social distancing protocol has been implemented by the President. Following the …

Automatically inferring user demographics from social media posts is useful for both social
science research and a range of downstream applications in marketing and politics. We …

Public health thrives on high-quality evidence, yet acquiring meaningful data on a
population remains a central challenge of public health research and practice. Social …

Bipolar disorder, an illness characterized by manic and depressive episodes, affects more
than 60 million people worldwide. We present a preliminary study on bipolar disorder …

Social media analysis frequently requires tools that can automatically infer demographics to
contextualize trends. These tools often require hundreds of user-authored messages for …

The development of industry 4.0 technologies makes it possible to create fundamentally new
technologies and systems based on the rapid development of computing resources. The …

Written language contains stylistic cues that can be exploited to automatically infer a variety
of potentially sensitive author information. Adversarial stylometry intends to attack such …

Computational social science studies often contextualize content analysis within standard
demographics. Since demographics are unavailable on many social media platforms (eg …