@inproceedings{3d620180be5b42d6b6bd2c171afb003e,
title = "Emotion analysis of Arabic articles and its impact on identifying the author's gender",
abstract = "The Gender Identification (GI) problem is concerned with determining the gender of the author of a given text based on its contents. The GI problem is one of the authorship profiling problems which have a wide range of applications in various fields such as marketing and security. Due to its importance, extensive research efforts have been invested in the GI problem for different languages. Unfortunately, the same cannot be said about the Arabic language despite its strategic importance and widespread. In this work, we explore the GI problem for Arabic text as a supervised learning problem. Specifically, we consider and compare two approaches for feature extraction. The first one is the Bag-Of-Words (BOW) approach while the second one is based on computing features related to sentiments and emotions. One goal of this work is to confirm the validity of the common stereotype that female authors tend to write in a more emotional way than male authors. Our results show that there is no conclusive evidence that this is true for our dataset.",
keywords = "Arabic text analysis, bag-of-words, emotions lexicons, gender identification, sentiments lexicons",
author = "Kholoud Alsmearat and Mohammed Shehab and Mahmoud Al-Ayyoub and Riyad Al-Shalabi and Ghassan Kanaan",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE/ACS International Conference of Computer Systems and Applications, AICCSA 2015 ; Conference date: 17-11-2015 Through 20-11-2015",
year = "2016",
month = jul,
day = "7",
doi = "10.1109/AICCSA.2015.7507196",
language = "English",
series = "Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA",
publisher = "IEEE Computer Society",
booktitle = "2015 IEEE/ACS 12th International Conference of Computer Systems and Applications, AICCSA 2015",
address = "United States",
}