Cognitive-inspired domain adaptation of sentiment lexicons
Sentiment lexicons are essential tools for polarity classification and opinion mining. In contrast to machine learning methods that only leverage text features or raw text for sentiment analysis, methods that use sentiment lexicons embrace higher interpretability. Although a number of domain-specifi...
Saved in:
Main Authors: | Xing, Frank Z., Pallucchini, Filippo, Cambria, Erik |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/151125 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Sentix: An aspect and domain sensitive sentiment lexicon
by: Lek, H.H., et al.
Published: (2014) -
Lexicons in sentiment analytics
by: YUAN, B., et al.
Published: (2017) -
Feature ensemble plus sample selection: Domain adaptation for sentiment classification
by: Xia, R., et al.
Published: (2014) -
Lexicon knowledge extraction with sentiment polarity computation
by: WANG, Zhaoxia, et al.
Published: (2016) -
Soft labeling constraint for generalizing from sentiments in single domain
by: Roy, Abhinaba, et al.
Published: (2022)