NileTMRG at SemEval-2017 Task 4: Arabic Sentiment Analysis

10/23/2017
by   Samhaa R. El-Beltagy, et al.
0

This paper describes two systems that were used by the authors for addressing Arabic Sentiment Analysis as part of SemEval-2017, task 4. The authors participated in three Arabic related subtasks which are: Subtask A (Message Polarity Classification), Sub-task B (Topic-Based Message Polarity classification) and Subtask D (Tweet quantification) using the team name of NileTMRG. For subtask A, we made use of our previously developed sentiment analyzer which we augmented with a scored lexicon. For subtasks B and D, we used an ensemble of three different classifiers. The first classifier was a convolutional neural network for which we trained (word2vec) word embeddings. The second classifier consisted of a MultiLayer Perceptron, while the third classifier was a Logistic regression model that takes the same input as the second classifier. Voting between the three classifiers was used to determine the final outcome. The output from task B, was quantified to produce the results for task D. In all three Arabic related tasks in which NileTMRG participated, the team ranked at number one.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/15/2021

Sentiment Analysis in Poems in Misurata Sub-dialect – A Sentiment Detection in an Arabic Sub-dialect

Over the recent decades, there has been a significant increase and devel...
research
04/07/2017

NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis

This paper describes our multi-view ensemble approach to SemEval-2017 Ta...
research
05/14/2020

NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to tackle Internet Humor

The paper describes the systems submitted to SemEval-2020 Task 8: Memoti...
research
11/29/2018

EvoMSA: A Multilingual Evolutionary Approach for Sentiment Analysis

Sentiment analysis (SA) is a task related to understanding people's feel...
research
09/09/2016

INSIGHT-1 at SemEval-2016 Task 4: Convolutional Neural Networks for Sentiment Classification and Quantification

This paper describes our deep learning-based approach to sentiment analy...
research
05/24/2022

Multilevel sentiment analysis in arabic

In this study, we aimed to improve the performance results of Arabic sen...
research
06/14/2016

TwiSE at SemEval-2016 Task 4: Twitter Sentiment Classification

This paper describes the participation of the team "TwiSE" in the SemEva...

Please sign up or login with your details

Forgot password? Click here to reset