Can Social Media Posts Predict Mental Illness?

We are all aware that marketing firms collect huge amounts of data to develop ad campaigns and to identify target audiences for marketing purposes. They use massive amounts of data in search of patterns and trends to assist them in creating and perfecting their products and services. Collecting and analyzing data has become a common practice worldwide.

There are growing ethical concerns regarding how this information is collected and how it is being used. The general public is painfully aware that our information is bought, sold and traded for a variety of reasons—some nefarious and wicked. As our concerns continue to mount and are compounded by reports criminals robbing these information warehouses of enormous amounts of valuable data, it is refreshing to know that there are those who seek to use this information for good and not evil.

The same way marketers and big business have been gathering and analyzing data—so to have governments, scientists and law enforcement agencies. These entities harvest and collect data for a variety of reasons.

Large amounts of personal information are collected and used in the prediction and containment of epidemics and also aid in the prevention of cyber terrorism, identity theft and a host of other web-based crimes and societal threats. For example, for the past few years, scientist have been able to pinpoint flu outbreaks by simply tracking the amount of people who goolgled “flu.”

In a study of social media sharing, University of Pennsylvania psychologist Andrew Schwartz, has found that most posts—especially by women—contain emotional language. Schwartz and his team study social media, posts and updates in an effort to learn about people. By studying the information shared via these platforms, he believes a general understanding of the physical and mental well-being of individuals and communities can be gained. Schwartz further explains that by analyzing an individual’s Facebook profile or Twitter feed he can accurately predict intimate traits about that person that are not being revealed intentionally.

Canadian and French researchers have partnered and are attempting to develop an algorithm that can catch warning signs and possibly predict dangerous behaviors. University of Ottawa’s Diana Inkpen has developed a project called “Social Web Mining and Sentiment Analysis For Mental Illness Detection.” Essentially, what Inkpen and her team are attempting to do is develop an algorithm that screens online posts for warning signs of mental illness. It is the goal of this team to create a set of tools that doctors, psychologists, counselors and mental health professionals can use to identify concerning or dangerous patterns by using social media posts.

This type of information gathering—while it may seem creepy and horribly invasive, is proving to be pivotal in the effort to make our world a slightly safer place.

Featured Image by Yoel Ben-Avaraham on Flickr available for use under Creative Commons License 2.0

Denise is currently a writer and editor for a federal agency in Washington, DC. Prior to that she served as an elementary and middle school teacher in Charleston, SC. She is an open-minded free spirit always read for new adventures. She enjoys traveling and relishes being exposed to alternate points of view. She is passionate about what she does and does everything passionately. Faith, family and finances are the core of her value system. She follows her own path and marches to her own beat. She is a dream chaser and with her husband and best friend by her side, she plans to take over the world.