Can Lexicon-Based Sentiment Analysis Boost Performances of Transformer-Based Models?-Reference-Cited by-同舟云学术

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Can Lexicon-Based Sentiment Analysis Boost Performances of Transformer-Based Models?

Published:2023-12-06 Issue: Volume: Page:314-319
ISSN:
Container-title:2023 7th International Conference on New Media Studies (CONMEDIA)
language:
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Author:

Manik Lindung Parningotan¹,Susianto Harry²,Dinakaramani Arawinda³,Pramanik Niken⁴,Suhardijanto Totok

Affiliation:

1. National Research and Innovation Agency,Research Center for Data and Information Sciences,Bandung,Indonesia

2. University of Indonesia,Faculty of Psychology,Depok,Indonesia

3. University of Indonesia,Faculty of Computer Science,Depok,Indonesia

4. University of Indonesia,Faculty of Humanities,Department of Linguistics,Depok,Indonesia

Funder

The University of Indonesia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10428117/10428106/10428401.pdf?arnumber=10428401

Reference15 articles.

1. On the Role of Text Preprocessing in BERT Embedding-based DNNs for Classifying Informal Texts

2. Out-of-Scope Intent Detection on A Knowledge-Based Chatbot

3. Aspect-Based Sentiment Analysis on Candidate Character Traits in Indonesian Presidential Election

4. Detecting Traces of Self-harm in Social Media: A Simple and Interpretable Approach

5. DNet: A lightweight and efficient model for aspect based sentiment analysis

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