@inproceedings{981d45fa7e114798bbfd3ba14bb95774,
title = "Multi-Label Emotion Classification for Arabic Tweets",
abstract = "Emotion Analysis (EA)is a process of determining if the text has any emotion. EA spread significantly in the recent years, especially for social media applications as applied to tweets and Facebook posts. An assumption has been presented recently that each social media post has no intensity or has one emotion. Different cases for public posts have been considered in this work, it focuses on several emotions (multi-label)included in a single post. Tweeter posts (Tweets)have been employed to validate the proposed work, it is possible to have different intensities related to each tweet (multi-target). The proposed work focused on Arabic language tweets unlike previously implemented work, which focused on other languages such as English or Chinese. A multi-label multi-target data set of Arabic tweets annotated for emotion analysis has been built, and different experts participated in the annotation process and Cohens Kappa measure was employed to determine their concordance.",
keywords = "Arabic Tweets, Emotion Analysis, Multi-Target Multi-Label Approach, Social Media, Tweet Readers",
author = "Shadi Alzu'Bi and Omar Badarneh and Bilal Hawashin and Mahmoud Al-Ayyoub and Nouh Alhindawi and Yaser Jararweh",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 6th International Conference on Social Networks Analysis, Management and Security, SNAMS 2019 ; Conference date: 22-10-2019 Through 25-10-2019",
year = "2019",
month = oct,
doi = "10.1109/SNAMS.2019.8931715",
language = "English",
series = "2019 6th International Conference on Social Networks Analysis, Management and Security, SNAMS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "499--504",
editor = "Mohammad Alsmirat and Yaser Jararweh",
booktitle = "2019 6th International Conference on Social Networks Analysis, Management and Security, SNAMS 2019",
address = "United States",
}