Automatic Compilation of Resources for Academic Writing and Evaluating with Informal Word Identification and Paraphrasing System

Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 5896–5904 Marseille, 11–16 May 2020 c⃝ European Language Resources Association (ELRA), licensed under CC-BY-NC 5896 Automatic Compilation of Resources for Academic Writing and Evaluating with Informal Word Identification and Paraphrasing System Seid Muhie Yimam1, Gopalakrishnan Venkatesh2, John Sie Yuen Lee3 and Chris Biemann1 Universit¨at Hamburg, Germany1, International Institute of Information Technology, Bangalore, India2, City University of Hong Kong, Hong Kong SAR3 yimam@informatik.uni-hamburg.de Abstract We present the first approach to automatically building resources for academic writing. The aim is to build a writing aid system that automatically edits a text so that it better adheres to the academic style of writing. On top of existing academic resources, such as the Corpus of Contemporary American English (COCA) academic Word List, the New Academic Word List, and the Academic Collocation List, we also explore how to dynamically build such resources that would be used to automatically identify informal or non-academic words or phrases. The resources are compiled using different generic approaches that can be extended for different domains and languages. We describe the evaluation of resources with a system implementation. The system consists of an informal word identification (IWI), academic candidate paraphrase generation, and paraphrase ranking components. To generate candidates and rank them in context, we have used the PPDB and WordNet paraphrase resources. We use the Concepts in Context (CoInCO) ”All-Words” lexical substitution dataset both for the informal word identification and paraphrase generation experiments. Our informal word identification component achieves an F-1 score of 82%, significantly outperforming a stratified classifier baseline. The main contribution of this work is a domain-independent methodology to build targeted resources for writing aids. Keywords: academic writing, academic word, academic phrase, informal word identification, academic text paraphrasing 1 Introduction We present the first approach to building resources for an academic writing aid system automatically. Academic writ- ing aid systems help in automatically editing a text so that it better adheres to the academic style of writing, partic- ularly by choosing a better academic word in a given do- main. In the context of academic paraphrasing tasks, the resources are mainly words or phrases, that are more ap- propriate to use in an academic writing style. Moreover, the academic resources might vary from domain to domain as some words or phrases are extensively used in one do- main over the other. The first step in building an academic writing aid tool is to collect resources that determines whether a given phrase follows the style of writing in academia. This involves an- alyzing a given sentence and determining if the lexemes of the sentences are well-selected academic words and phrases or not. To evaluate the resources compiled, we have to build a sys- tem, analogous to the lexical substitution and text simpli- fication tasks, for example, (Szarvas et al., 2013; ˇStajner and Saggion, 2018), that consists of informal word identifi- cation, academic candidate generation, and candidate para- phrase ranking components (see Figure 1). While it is pos- …

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