@inproceedings{ada7b81a76fd430ebe383dcd9d919bab,
title = "Investigate human behavior during ramadan through network structure: Evidence from Twitter",
abstract = "This paper studies online behavior during the holy month of Ramadan as reflected in tweeting patterns on the popular social media platform Twitter. In the first study of its kind using Twitter data from the United Arab Emirates (UAE), interaction networks before, during and after Ramadan are extracted and analyzed. We examine the network structure via the field decomposition of Weakly Connected Components (WCC), degree distribution, degree mixing, clustering distribution, clustering mixing and diameter statistics. A number of interesting structural features were detected which were subjected to further analysis. Some of these are common to the entire dataset while others were unique to specific periods (either during Ramadan, or in the two adjacent months). While preliminary in nature, these results were extremely promising and strongly motivate subsequent research efforts on this topic.",
keywords = "Big Data, Ramadan, Social Network Analysis, Twitter, United Arab Emirates",
author = "Al-Shehhi, {A. M.} and Woon, {W. L.} and Z. Aung",
note = "Funding Information: This research work was funded by Masdar Institute of Science and Technology, Khalifa University of Science and Technology, Abu-Dhabi, United Arab Emirates. Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 ; Conference date: 10-12-2017 Through 13-12-2017",
year = "2018",
month = feb,
day = "9",
doi = "10.1109/IEEM.2017.8290006",
language = "British English",
series = "IEEE International Conference on Industrial Engineering and Engineering Management",
publisher = "IEEE Computer Society",
pages = "823--827",
booktitle = "2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017",
address = "United States",
}