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"Data Envelopment Analysis of linguistic features and passage relevance" by Bahadorreza Ofoghi, Mahdi Mahdiloo et al.

Question Answering (QA) systems play an important role in today's human–computer interaction systems. QA performance can be significantly improved using effective answer passage retrieval and ranking techniques. Our focus in this paper is on both non machine learning-based and deep learning-based passage retrieval and ranking systems for QA to leverage linguistic features within the text of questions and passages and improve passage ranking effectiveness. We propose a decoupled linguistic...
Data Envelopment Analysis Linguistic Features Passage Ranking Question Answering
Source: uow.edu.au

Frontiers | To Be Ethical and Responsible Digital Citizens or Not: A Linguistic Analysis of Cyberbullying on Social Media

As a worldwide epidemic in the digital age, cyberbullying is a pertinent but understudied concern—especially from the perspective of language. Elucidating the linguistic features of cyberbullying is critical both to preventing it and to cultivating ethical and responsible digital citizens. In this study, a mixed-method approach integrating lexical feature analysis, sentiment polarity analysis, and semantic network analysis was adopted to develop a deeper understanding of cyberbullying language...
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