Ask Me or Tell Me? Enhancing the Effectiveness of Crowdsourced Design Feedback

01/15/2021
by   Fritz Lekschas, et al.
0

Crowdsourced design feedback systems are emerging resources for getting large amounts of feedback in a short period of time. Traditionally, the feedback comes in the form of a declarative statement, which often contains positive or negative sentiment. Prior research has shown that overly negative or positive sentiment can strongly influence the perceived usefulness and acceptance of feedback and, subsequently, lead to ineffective design revisions. To enhance the effectiveness of crowdsourced design feedback, we investigate a new approach for mitigating the effects of negative or positive feedback by combining open-ended and thought-provoking questions with declarative feedback statements. We conducted two user studies to assess the effects of question-based feedback on the sentiment and quality of design revisions in the context of graphic design. We found that crowdsourced question-based feedback contains more neutral sentiment than statement-based feedback. Moreover, we provide evidence that presenting feedback as questions followed by statements leads to better design revisions than question- or statement-based feedback alone.

READ FULL TEXT

page 2

page 10

research
04/09/2022

Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback

News recommendation is different from movie or e-commercial recommendati...
research
01/20/2021

Hardhats and Bungaloos: Comparing Crowdsourced Design Feedback with Peer Design Feedback in the Classroom

Feedback is an important aspect of design education, and crowdsourcing h...
research
05/06/2014

How Community Feedback Shapes User Behavior

Social media systems rely on user feedback and rating mechanisms for per...
research
02/24/2021

Equal Affection or Random Selection: the Quality of Subjective Feedback from a Group Perspective

In the setting where a group of agents is asked a single subjective mult...
research
07/04/2022

Meetings and Mood – Related or Not? Insights from Student Software Projects

Background: Teamwork, coordination, and communication are a prerequisite...
research
06/26/2015

Humor in Collective Discourse: Unsupervised Funniness Detection in the New Yorker Cartoon Caption Contest

The New Yorker publishes a weekly captionless cartoon. More than 5,000 r...
research
09/28/2020

Learning Classifiers under Delayed Feedback with a Time Window Assumption

We consider training a binary classifier under delayed feedback (DF Lear...

Please sign up or login with your details

Forgot password? Click here to reset