UX Research: Misinformation on TikTok & Instagram Reels

Overview

Our semester-long project in SMAD 327 involved researching design methods to prevent the spread of misinformation on TikTok and Instagram Reels. With the term “fake news” gaining prominence in recent years, understanding the efficiency of current design solutions on short video-sharing apps is important, as most research focuses on apps like Facebook and Twitter.

The Process

1

Discover

Research Goals, Research Questions, Literature Review

2

Test

Screening survey, Building Rapport, Thing Aloud, Semi-Structured Interview

3

Analyze

NVIVO findings, Themes, Design Recommendations, Conclusion

The Problem

As mentioned before, there’s very little research on design solutions to combat misinformation on TikTok and Instagram Reels. My main goal was to focus on the warning labels the applications already have and test their effectiveness.

Research Questions

  1. What strategies do short video sharing platforms use to combat misinformation?

  2. How do people react to countermeasures on TikTok and Instagram Reels?

  3. How do people perceive the countermeasures and how does fact-checking influence their evaluation of the information on TikTok and Instagram Reels

  4. How effective are those strategies to reduce the sharing of misinformation?

Literature Review Results

I read three empirical research articles and found that there’s little research and the research that is there pertains only to the U.S. The main issue highlighted was that warning labels aren’t specific enough.

Interviews

Highlights:

I interviewed two students who used TikTok daily and found out about their perspective on fake news and how trusting they were of social media platforms.

The most beneficial part of the interviews was the Think Aloud portion, where interviewees would watch TikToks. Interviewees watched a total of six videos: two being “fake news” without labels, two being real news without labels, and two being fake news with warning labels.

Insightful Findings

  • The most clicked feature among the interviewees were the comments

  • Both interviewees didn’t see the warning labels until after watching the video

  • The most effective design strategy to combat misinformation is using a blurred screen warning

Design Recommendations:

  • Make warning labels more specific to content

  • Specify and explain the different classifications of warnings (ex. partially false, false, etc.)

  • Filter through misinformation in the comments

  • Make red warning labels brighter/more noticeable

Themes:

  1. Pathway & Engagement: watch flow and features that were/weren’t interacted with

  2. Credibility Judgment: attitudes towards fake news, political party influence

Thanks for reading!