CLexIS2: A New Corpus for Complex Word Identification Research in Computing Studies

Proceedings of Recent Advances in Natural Language Processing, pages 1075–1083 Sep 1–3, 2021. https://doi.org/10.26615/978-954-452-072-4_121 1075 CLexIS2: A New Corpus for Complex Word Identification Research in Computing Studies Jenny A. Ortiz-Zambrano Universidad de Guayaquil Guayaquil, Ecuador jenny.ortizz@ug.edu.ec Arturo Montejo-Ra´ez CEATIC - Universidad de Ja´en Ja´en, Spain amontejo@ujaen.es Abstract Reading is a complex process not only because of the words or sections that are difficult for the reader to understand. Complex word iden- tification (CWI) is the task of detecting in the content of documents the words that are diffi- cult or complex to understand by the people of a certain group. Annotated corpora for En- glish learners are widely available, while they are less common for the Spanish language. In this article, we present CLexIS2, a new corpus in Spanish to contribute to the advancement of research in the area of Lexical Simplification, specifically in the identification and prediction of complex words in computing studies. Sev- eral metrics used to evaluate the complexity of texts in Spanish were applied, such as LC, LDI, ILFW, SSR, SCI, ASL, CS. Furthermore, as a baseline of the primer, two experiments have been performed to predict the complex- ity of words: one using a supervised learning approach and the other using an unsupervised solution based on the frequency of words on a general corpus. 1 Introduction Reading is a complex process not only because of the words or sections that are difficult for the reader to understand. Therefore, an adequate understand- ing of the content of the texts is required to be able to create coherent mental representations and this way to be able to capture their content (van den Broek, 2010). Information technologies make it possible for people to access abundant information in different areas such as education, news, social, health, or government, among others. However, this informa- tion is not accessible to many, since some people face great reading barriers such as long sentences, unusual words, or complex linguistic structures that do not allow them to understand the content of the texts, with people with intellectual disabilities and people being directly affected in learning; includ- ing university students, who are people with a high educational level and specialized knowledge in dif- ferent subjects of study but, still, could be part of groups of people with reading disabilities (Alarc´on et al., 2020). Complex Word Identification (CWI) is the task of detecting words in the contents of texts that are difficult or complex for people in a certain group to understand (Rico-Sulayes, 2020). CWI and the substitution of words identified as complex may significantly improve readability and understand- ability of a given text (Zotova et al., 2020). In recent years, CWI has become an area of great interest for the scientific community and re- searchers in computational linguistics proposing development of computational semantic analysis systems as evidenced by the shared tasks of CWI by (Paetzold and Specia, 2016) in SemEval 2016, and NAACL-HTL 2018 by (Yimam et al., 2018), the task of the CWI of …

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