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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Annotated Corpus of Mesopotamian-Iraqi Dialect for Sentiment Analysis in Social Media

Author 1: Al-Khafaji Ali J Askar
Author 2: Nilam Nur Amir Sjarif

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120413

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 4, 2021.

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Abstract: Research on Sentiment Analysis in social media by using Mesopotamian-Iraqi Dialect (MID) of Arabic language was rarely found, there is no reliable dataset developed in MID neither an annotated corpus for the sentiment analysis of social media in this dialect. Therefore, this gap was the main stumbling block for researchers of sentiment analysis in MID, for this reason, this paper introduced the development of an annotated corpus of Mesopotamian-Iraqi Dialect for sentiment analysis in social media and named it as (ACMID) stands for (the annotated corpus of Mesopotamian-Iraqi Dialect) to help researchers in future for using this corpus for their studies, to the best of our knowledge this is the first annotated corpus that both classify polarity as well as emotion classification in MID. Likewise, Facebook as the most popular social platform among Iraqis was used to extract the data from its popular Iraqi pages. 5000 comments were extracted from these pages classified by its polarity (Positive, Negative, Neutral, Spam) by two Iraqi annotators, these annotators were simultaneously classifying the same comments according to Ekman seven universal emotions (Anger, Fear, Disgust, Happiness, Sadness, Surprise, Contempt) or no emotion. Cohen's kappa coefficient was then used to compare the two annotators’ results to find the reliability of these results. The data shows a comparable value among the two annotators for the polarity classification as high as 0.82, while for the emotion classification the result was 0.65.

Keywords: Sentiment analysis; Mesopotamian dialect; Iraqi dialect; social media; annotated corpus; emotion classification; Arabic language

Al-Khafaji Ali J Askar and Nilam Nur Amir Sjarif, “Annotated Corpus of Mesopotamian-Iraqi Dialect for Sentiment Analysis in Social Media” International Journal of Advanced Computer Science and Applications(IJACSA), 12(4), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120413

@article{Askar2021,
title = {Annotated Corpus of Mesopotamian-Iraqi Dialect for Sentiment Analysis in Social Media},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120413},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120413},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {4},
author = {Al-Khafaji Ali J Askar and Nilam Nur Amir Sjarif}
}


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