Hi, I’m Ryuhaerang Choi from KAIST. In this presentation, I’ll present our CSCW paper; You Are Not Alone: How Trending Stress Topics Brought #Awareness and #Resonance on Campus.
When you’re going through a tough time, It helps to relieve stress to open up and share the stressful experiences with others, such as family and friends.
Having someone to listen is helpful, but attention and empathy give more relief and a feeling of "I’m not the only one."
To simply vent negative emotions or disclose vulnerable and stigmatized experiences, people are turning to social media and online communities, such as Reddit, Facebook, and TalkLife.
However, in most existing platforms, individual posts with similar content are separated and could be lost in a large number of posts from a diverse set of users.
Therefore, a post that needs timely responses could often be neglected and not receive prompt attention and engagement.
How can technology be leveraged to support people recognizing and acquiring attention and engagement from peers who are experiencing or have been through similar stress?
We focus on that there are many shared stressors among local community members.
To this end, we introduce StressTrendmeter, a mobile app for university students to
anonymously share the source of stress via the form of hashtags, and
follow stress trends based on students’ empathy for each hashtag.
To concretize the design directions, we conducted two interviews with university stakeholders,
a psychotherapist and the associate vice president of student welfare at KAIST.
The interview questions are made to identify current online channels where students disclose their stressful experiences
and challenges in understanding students’ stress and supporting the students.
Both interviewees suggested that offering collective information about students’ stress could help students relieve stress
and college administrators identify campus issues and provide tangible support.
To this end, we set two design goals to build StressTrendmeter.
First, facilitate social sharing of stressful experiences by incorporating three important factors,
(i) anonymity, (ii) peer support, and (iii) sympathetic reactions, which have been emphasized in the literature.
Second, enable users to easily be aware of common stressful experiences on campus at that period of time.
To allow instant stress venting, we leveraged hashtag format.
Students can share a detailed story about a hashtagged stress topic via comment.
By sharing only stress topics in hashtag format, we expected that students quickly explore other people's stress,
anonymity is enhanced as shared experience loses details,
and the likelihood that a topic will be empathized increase.
Moreover, to make empathy recognizable online, which facilitates sharing stress,
we incorporated an empathy button to instantly express empathy and visualize others’ empathy.
These two design components are for encouraging spontaneous and instant sharing of stressful experiences in StressTrendmeter.
To foster social interaction among people with similar experiences,
we provided demographic-based sub-communities to gather students with more common experiences.
We also provided topic-based anonymous chatrooms
so students could discuss with others experiencing or have experienced the stress.
To take the timeliness of stress topics into account, StressTrendmeter ranks stress topics based on empathy counts from students.
We believe that displaying trending topics helps students to easily recognize
which stressful experiences are empathized now by the community members.
In our user study, 222 university students from KAIST and SNU participated.
Participants responded to the preliminary survey about the awareness of other students’ stress
and then started using StressTrendmeter for at least four weeks.
After that, they submitted a post survey about the awareness and experiences using StressTrendmeter,
and 30 randomly selected participants were invited to semi-structured interviews.
In this presentation, we report two highlights of the findings.
First, at an individual level, students’ stress awareness and self-care increased.
Second, at a community level, students, as community members, resonated and got accountability to care for others.
Using hashtags made students concisely describe complex situations in a few words,
making them reflect upon the intrinsic stressors.
Students also could grasp the trending stress factors in the community at a glance via quickly browsing trending hashtags,
and recognize that their peers are experiencing similar stress.
From the awareness of one’s and other students' stress,
students could compare their situations with others and feel relief from assessing their situation better.
They also could learn about others’ experiences that they would likely experience in the future, bringing the stress-buffering effect.
At a community level, the awareness of others’ stress led to actions for social support,
such as expressing empathy via the empathy button
and leaving supportive comments by feeling the accountability of caring for others.
Such enacted supportive action from awareness is called reactive resonance.
The resonance and accountability strengthened students’ community attachment by fostering the feeling of "I’m not the only one."
Based on these findings, we drew three main design implications for social interaction design among community members.
The first is exploring what information needs to be visible
and how to make the information translucent within a community.
For example, one can examine different visualizations of individuals’ emotional experiences,
such as an emotion map that can promote a sense of proximity or an emotion thermometer.
The second one is balancing the simplicity of user interactions and contextual specificity of social sharing.
For example, one can provide phased social interactions, starting from lighthearted to in-depth interactions depending on a user’s needs.
The third one is strengthening social ties and community identity to foster commitment for content moderation in a system for discussing negative topics.
For instance, community-based systems could foster offline identity-based commitment
or grant a shared identity to users while guaranteeing anonymity within the system.
Here is a summary of our contributions and key findings.
We introduce a topic- and trending-based community design for building awareness of stressful experiences
and for supporting social interactions among peers with similar experiences.
We provide empirical findings from a large in-the-wild deployment study
on how stress topic trends and topic-based social groups affect individuals and the community.
We present design implications on how topic- and trending-based social interactions could foster
community awareness, resonance, and accountability that can facilitate social support.
Please refer to our paper for more details and interesting findings that we could not cover in this presentation.
I’m happy to take any questions or have a chat about our work.
So if you’re interested, please send me an email or join the discussion at the conference.
Thank you.