Evaluating aspect-based sentiment classification on Twitter hate speech using neural networks and word embedding features
In this paper, a neural network is proposed to analyse Twitter sentiment classification for the Twitter domain. The study examines and evaluates the performance of neural networks with word embedding features in Twitter sentiment classification. Four benchmark datasets were used to represent differe...
Published in: | Frontiers in Artificial Intelligence and Applications |
---|---|
Main Author: | Zainuddin N.; Selamat A.; Ibrahim R. |
Format: | Conference paper |
Language: | English |
Published: |
IOS Press BV
2018
|
Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063377228&doi=10.3233%2f978-1-61499-900-3-723&partnerID=40&md5=06b19da482304287abdd18fe2e76983a |
Similar Items
-
Hate crime on twitter: Aspect-based sentiment analysis approach
by: Zainuddin N.; Selamat A.; Ibrahim R.
Published: (2019) -
Discovering Hate Sentiment within Twitter Data through Aspect-Based Sentiment Analysis
by: Zainuddin N.; Selamat A.; Ibrahim R.
Published: (2020) -
Aspect-Based Classification and Visualization of Twitter Sentiment Analysis Towards Online Food Delivery Services in Malaysia
by: Samah K.A.F.A.; Jailani N.S.; Hamzah R.; Aminuddin R.; Abidin N.A.Z.; Riza L.S.
Published: (2024) -
The quantification of speech intelligibility of Malay words by means of corner vowels
by: Asyafi’Ie bin Ahmad M.A.; Harun M.; Ibrahim M.N.; Shapiai M.I.; Khalid P.; Hamid S.
Published: (2016) -
Phoneme-based or isolated-word modeling speech recognition system? An overview
by: Yusnita M.A.; Paulraj M.P.; Yaacob S.; Abu Bakar S.; Saidatul A.; Abdullah A.N.
Published: (2011)