Optimizing the reading experience for an interpersonal network map

Abstract

This Master of Art thesis aims to optimize the reading experience for an interpersonal network map in mobile devices, the reason for focusing on mobile devices, is based on the 2017 Pew Research Center report, 85% of U.S adults now get their news on a mobile device, and from the research of Eric Enge, mobile usage in total internet traffic reached 63% in 2017 in the US. The trend of mobile-centered seems to continuously grow in the near future.

During the literature review and the user studies, it provided a fundamental knowledge base of how user interact and respond to the graphical user interface in sociogram. The findings offer the framework of the prototype. Visual experiments of the interpersonal network map and user interface wireframes had gone through rounds of design iteration with the user group closely. Target user validations and prototype testing provide positive result.

At last, the research question was answered. The design and development team can follow those practical design guidelines (A) Personalization: customized to personal need and expectation (B) Environmental adaptation system: automatically switch the brightness and the UI color contrast, based on the reading environment or reader’s personal preference. (C) Automatic Map tutorial: lowering the learning curve for readers. (D) Minimize cognitive load: with limited information shown, improve the efficiency of reading. (E) Organic visual language: easier for the user to connect the visuals with the human relationship. (F) Incentivize reading experience: give the user a timely respond on certain interaction. Those design guidelines for the interpersonal network map in mobile devices, can also be applied for other related areas, particularly in displaying infographic in digital mobile devices.