Team
Lily Ting, Mia Tang, Victor Huang (me) & Theo Mandin-Lee
Our team is adorably named Lagrange Mean Value Theorem (LMVT)
My roles
- UX Researcher, contributed in UX research by interviewing users and gathering insights
- Project Manager, timelined & facilitated progress for deliverables
Social media users come across ads and posts everyday when they’re scrolling through their news feed, and occasionally report them. But what happens after they report, and how do they feel?
Our solution, ReportChat, replaces the generic, nondescript pop-ups that make users feel ignored with a chatbot that makes them feel heard, empowered, and impactful.
How might we incentivize users to report algorithmic biased ads?
Walk the wall of findings and insights from research
We used generative and evaluative research methods to learn more about users’ experience with reporting posts and ads on social media. In total, we interviewed 8 users, specifically those who have reported ads / posts before.
- Generative Think-Aloud
- Directed Storytelling
- Semi-structured Interviews
Talking with users and sharing potential solutions uncovered their pain points and unmet needs when using these types of features. We utilized affinity diagrams and empathy maps to help come up with insights from our findings.
Crazy 8s by each team member
To generate our solutions, we utilized crazy 8s & storyboarding. We then used speed-dating to validate our solutions & user needs with 4 additional users.
” I feel annoyed [after reporting an ad], because [the website] gives no feedback. [The report] probably goes into some massive database”
“I don’t feel like I had a big impact”
“I like to feel a little sense of victory.”
“If there was little to no feedback [then I would not report an ad]. Weak feedback gives me the impression that this app doesn’t do anything about the report.”
“I am just trying to get through the report action as fast as possible, [and I] didn’t really care about the other features surrounding it”
1. Reporting ads is an emotional experience
People that are indifferent to ads keep scrolling, rather than stop and take action. A main motivation for reporting ads is annoyance, anger, or punishment.
2. People want to feel like their report made a difference
On most social media, there is not strong enough feedback from the company that their report will make any dent in the world. People want to feel empowered after they report ads
3. People don’t want to do extra work to accomplish their goals
User don’t want to have to go through a lengthy report process, and will quit the reporting process if they are faced with a long form that they need to fill up.
To address the most pressing user needs of better feedback and helping them feel like they are making an impact all while balancing with the need for them to not feel like they are doing extra work, we propose an optional chat-bot that appears after a user reports an ad.
Users can select from options such as
- add report details
- view report status
- how algorithms work
users are able to review the reporting progress and refer to educational materials about algorithmic bias. What’s good about a chat-bot is that it allows the user to decide how much feedback they need to feel satisfied with the process.
