A meta-framework for modeling the human reading process in sentiment analysis
المؤلف | Baly, Ramy |
المؤلف | Hobeica, Roula |
المؤلف | Hajj, Hazem |
المؤلف | El-Hajj, Wassim |
المؤلف | Shaban, Khaled Bashir |
المؤلف | Al-Sallab, Ahmad |
تاريخ الإتاحة | 2021-09-01T10:02:39Z |
تاريخ النشر | 2016 |
اسم المنشور | ACM Transactions on Information Systems |
المصدر | Scopus |
الملخص | This article introduces a sentiment analysis approach that adopts the way humans read, interpret, and extract sentiment from text. Our motivation builds on the assumption that human interpretation should lead to the most accurate assessment of sentiment in text. We call this automated process Human Reading for Sentiment (HRS). Previous research in sentiment analysis has produced many frameworks that can fit one or more of the HRS aspects; however, none of these methods has addressed them all in one approach. HRS provides a meta-framework for developing new sentiment analysis methods or improving existing ones. The proposed framework provides a theoretical lens for zooming in and evaluating aspects of any sentiment analysis method to identify gaps for improvements towards matching the human reading process. Key steps in HRS include the automation of humans low-level and high-level cognitive text processing. This methodology paves the way towards the integration of psychology with computational linguistics and machine learning to employ models of pragmatics and discourse analysis for sentiment analysis. HRS is tested with two state-of-the-art methods; one is based on feature engineering, and the other is based on deep learning. HRS highlighted the gaps in both methods and showed improvements for both. 2016 ACM |
راعي المشروع | This work was made possible by NPRP 6-716-1-138 grant from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. |
اللغة | en |
الناشر | Association for Computing Machinery |
الموضوع | Automation Deep learning Sentiment analysis Supervised learning Text processing Automated process Discourse analysis Feature engineerings Human reading Meta-frameworks Notions Psychology Zooming-in Data mining |
النوع | Article |
رقم العدد | 1 |
رقم المجلد | 35 |
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