August 15, 2017
Rachel Kornfield
PhD Candidate
School of Journalism and Mass Communication
Research Assistant
University of Wisconsin-Madison
The words we say in daily conversation can provide a powerful window into our state of mind, including our moods, concerns, and priorities. General topics of discussion can be revealing (for example, if we’re talking about friends, the weather, or problems at work). But even more is often revealed by subtler styles of speech, including the pronouns we use, our emotional tone, and how we put our sentences together. These subtle linguistic differences are especially meaningful in an age when computers play an ever-increasing role in our lives. Technology and social media provide an array of new outlets through which to communicate. At the same time, computer science offers new tools to automatically measure subtle qualities of language. At the Center for Health Enhancement Systems Studies (CHESS), our research uses social media language not only to understand people better, but also to help people improve their health.The A-CHESS smartphone app provides addiction recovery services on-demand. Analyzing the language used in A-CHESS discussion forums is helping researchers predict the likelihood of relapse.
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| A-CHESS display |
For decades, our research center has been developing
evidence-based computerized systems to guide and support individuals as they
face different health challenges (e.g., cancer, aging). Recently, we have
focused our attention on addiction by developing
A-CHESS, a smartphone
application that provides a range of on-demand recovery services, including
self-help meeting directories, expert advice, games, and message forums that
participants can use to instantly connect to their peers. Within these forums,
participants can seek and provide support, or simply chat and build
relationships. Having access to on-demand information and social support, even
at 4am on a Tuesday, can make the challenges of recovery much more manageable.
Our research has shown that providing individuals with A-CHESS reduced their
heavy drinking, even a year later. However, until recently, we had not assessed
the particular types of language produced by participants communicating with
each other through A-CHESS.
As a doctoral candidate at CHESS, my research looks at how the language that individuals submit to online discussion boards can offer useful clues about future health and well-being. This research often involves very slowly coding messages by hand, but it can also involve computerized programs that automatically count dozens of subtle linguistic qualities in large bodies of text within seconds. Recently, we used a computer program called LIWC to identify a number of linguistic signals that precede episodes of risky drinking among A-CHESS participants....we found that those who went on to relapse show higher rates of swearing and negative emotion words in their messages, whereas those who did not relapse used more words related to achievements and information processing.
For instance, we found that those who went on to relapse show higher rates of swearing and negative emotion words in their messages, whereas those who did not relapse used more words related to achievements. Taken together, individuals’ styles of writing provided a better indicator of future recovery success than survey-based measures. The surveys involved asking participants to report their level of confidence, social issues, and demographic characteristics, and took a lot of time and effort for participants to complete. In other words, automated linguistic analysis may improve our ability to predict outcomes while also reducing burden on patients – a win – win!
(This research will be reported in more detail in a
forthcoming issue of Health Communication).
These linguistic insights also have practical applications
for improving tools like A-CHESS. While A-CHESS provides a range of on-demand
services, some individuals benefit from more personal attention. Knowing who is
struggling will allow us to intervene to help people when they need help the
most. We are already beginning to refine A-CHESS to do just this: In
collaboration with computer scientists and engineers, we have programmed
algorithms to run real-time scans of messages posted on the A-CHESS discussion
board, looking for concerning words, so that we can direct help to those who
need it, when they need it. For example, if a participant posts a message about
stronger-than-usual cravings, our algorithm may recognize familiar patterns of
words, which will alert a trained human moderator and allow her to respond by
offering emotional support, advice, or even calling the participant on the
phone.
Future research
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| A-CHESS word cloud |
Individuals who use A-CHESS have often remarked that writing
on the discussion forum has allowed them to get through their most difficult
moments. Even when they don’t get an instantaneous response, individuals feel
that they are sharing their thoughts, feelings, and concerns with an audience
who cares. And they are correct. Not only will their peers read and consider
their words, but the system itself is increasingly “listening” and responding,
allowing us provide better care to more people.
Read more about this research:
What Do You Say Before You Relapse? How Language Use in a Peer-to-peer Online Discussion Forum Predicts Risky Drinking among Those in Recovery
About our guest blogger:
Rachel Kornfield is a doctoral candidate in Mass Communication at the University of Wisconsin-Madison. Her research is aimed at better understanding how emerging communication technologies facilitate therapeutic self-disclosure and social support exchange in order to improve individuals’ health and well being. Rachel has worked with the Center for Health Enhancement System Studies on several projects examining how individuals benefit from A-CHESS, a new mobile application for substance use disorders.
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