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Wei Xu ([[University of Pennsylvania]]), Chris Callison-Burch ([[University of Pennsylvania]]), and Courtney Napoles ([[Johns Hopkins University]]) introduced the [[Newsela]] corpus to the academic field in 2015.<ref>{{cite journal |last1=Xu |first1=Wei |last2=Callison-Burch |first2=Chris |last3=Napoles |first3=Courtney |title=Problems in Current Text Simplification Research: New Data Can Help |journal=Transactions of the Association for Computational Linguistics |date=2015 |volume=3 |pages=283–297|doi=10.1162/tacl_a_00139 |s2cid=17817489 |doi-access=free }}</ref> The corpus is a collection of thousands of news articles professionally leveled to different reading complexities by professional editors at [[Newsela]]. The corpus was originally introduced for [[text simplification]] research, but was also used for text readability assessment.<ref>{{cite journal |last1=Deutsch |first1=Tovly |last2=Jasbi |first2=Masoud |last3=Shieber |first3=Stuart |title=Linguistic Features for Readability Assessment |journal=Proceedings of the Fifteenth Workshop on Innovative Use of NLP for Building Educational Applications |date=July 2020 |pages=1–17 |doi=10.18653/v1/2020.bea-1.1 |arxiv=2006.00377 |url=https://www.aclweb.org/anthology/2020.bea-1.1|doi-access=free }}</ref>
===Linguistic
====Semantic or Advanced Semantic====
Advanced semantic or semantic features' influence on text readability was pioneered by Bruce W. Lee during his study at the ([[University of Pennsylvania]]), in 2021. Whilst introducing his features hybridization method, he also explored handcrafted advanced semantic features which aim to measure the amount of knowledge contained in a given text.<ref>{{cite journal |last1=Lee |first1=Bruce W. |last2=Jang |first2=Yoo Sung |last3=Lee |first3=Jason Hyung-Jong |title=Pushing on Text Readability Assessment: A Transformer Meets Handcrafted Linguistic Features |journal=Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing |series=EMNLP '21 |date=November 2021 |pages=10669–10686 |doi=10.18653/v1/2021.emnlp-main.834 |s2cid=237940206 |url=https://aclanthology.org/2021.emnlp-main.834/|arxiv=2109.12258 }}</ref>
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