Comparison of fonts in dark mode

Abstract

Tamni način rada postaje sve popularniji u digitalnim korisničkim sučeljima, no njegova kombinacija s različitim fontovima može imati značajan utjecaj na čitkost teksta. Cilj ovog završnog rada bio je ispitati kako tipografija, točnije četiri različita fonta: Verdana, Georgia, Times New Roman i Arial, utječu na čitkost teksta u tamnom načinu rada. U teorijskom dijelu rada obrađena su osnovna tipografska načela, razlike među fontovima, te karakteristike tamnog načina rada. Praktični dio obuhvaća istraživanje u kojem je sudjelovalo 80 studenata koji su čitali tekstove na mobilnom uređaju s fiksnom tamnoplavom pozadinom (#15202b). Takva tamna pozadina se koristi u tamnoj temi na društvenoj mreži Twitter/X. Rezultati pokazuju da font Times New Roman ima najmanji broj pogrešaka i najkraće prosječno vrijeme čitanja, čime se izdvojio kao najčitkiji font u tamnom načinu rada. Font Georgia se, s druge strane, pokazao kao najzahtjevniji za čitanje, s najviše pogrešaka. Također, rezultati su pokazali razlike u čitanju između muškaraca i žena, pri čemu su žene brže i preciznije čitale tekst.Dark mode is becoming increasingly popular in digital interfaces, but its combination with different fonts can have a significant impact on text readability. The aim of this thesis was to examine how typography—specifically four different fonts: Verdana, Georgia, Times New Roman, and Arial—affects text legibility in dark mode. The theoretical part of the thesis covers the basic principles of typography, differences between fonts, and the characteristics of dark mode. The practical part includes a study involving 80 students who read texts on a mobile device with a fixed dark blue background (#15202b). This particular dark background is used in the dark theme on the social network Twitter/X. The results show that Times New Roman had the fewest errors and the shortest average reading time, making it the most legible font in a dark interface. Georgia, on the other hand, proved to be the most challenging to read, with the highest number of errors. The results also revealed differences in reading performance between men and women, with women generally reading faster and more accurately

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Last time updated on 17/07/2025

This paper was published in University North Digital Repository.

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