@inproceedings{f0402ee7a1264e8281c86e37dce9a591,
title = "Supercalifragilisticexpialidocious: Why Using the “Right” Readability Formula in Children{\textquoteright}s Web Search Matters",
abstract = " Readability is a core component of information retrieval (IR) tools as the complexity of a resource directly affects its relevance: a resource is only of use if the user can comprehend it. Even so, the link between readability and IR is often overlooked. As a step towards advancing knowledge on the influence of readability on IR, we focus on Web search for children . We explore how traditional formulas–which are simple, efficient, and portable–fare when applied to estimating the readability of Web resources for children written in English. We then present a formula well-suited for readability estimation of child-friendly Web resources. Lastly, we empirically show that readability can sway children{\textquoteright}s information access. Outcomes from this work reveal that: (i) for Web resources targeting children, a simple formula suffices as long as it considers contemporary terminology and audience requirements, and (ii) instead of turning to Flesch-Kincaid–a popular formula–the use of the “right” formula can shape Web search tools to best serve children. The work we present herein builds on three pillars: Audience, Application, and Expertise. It serves as a blueprint to place readability estimation methods that best apply to and inform IR applications serving varied audiences.",
keywords = "information retrieval, readability, relevance, web search",
author = "Garrett Allen and Ashlee Milton and Wright, {Katherine Landau} and Fails, {Jerry Alan} and Casey Kennington and Pera, {Maria Soledad}",
note = "Allen, Garrett; Milton, Ashlee; Wright, Katherine Landau; Fails, Jerry Alan; Kennington, Casey; and Pera, Maria Soledad. (2022). {"}Supercalifragilisticexpialidocious: Why Using the 'Right' Readability Formula in Children{\textquoteright}s Web Search Matters{"}. In Advances in Informational Retrieval (Lecture Notes in Computer Science series, Volume 13185, pp. 3-18). Springer. https://doi.org/10.1007/978-3-030-99736-6_1; 44th European Conference on Information Retrieval, ECIR 2022 ; Conference date: 10-04-2022 Through 14-04-2022",
year = "2022",
month = jan,
day = "1",
doi = "10.1007/978-3-030-99736-6_1",
language = "American English",
isbn = "9783030997359",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "3--18",
editor = "Matthias Hagen and Suzan Verberne and Craig Macdonald and Christin Seifert and Krisztian Balog and Kjetil N{\o}rv{\aa}g and Vinay Setty",
booktitle = "Advances in Informational Retrieval",
}