@inproceedings{193bb560386b4710ba70cf7f554c3058,
title = "Corpus Analysis of COVID-19 Related Loneliness on Twitter",
abstract = "Loneliness is a complex mental health issue involving feelings of isolation, disconnectedness, and a lack of purpose in life. The coronavirus disease-19 (COVID-19) pandemic and lockdowns significantly increased social isolation, contributing to a global rise in loneliness on social online platforms. However, research on mental health expressions in Arabic on social media is limited, exacerbating the lack of understanding of loneliness and mental health issues in these communities. Stigma and societal resistance in the Middle East hinder individuals from seeking mental health support, particularly noticeable amidst the challenges of the pandemic. Thus, this study aimed to conduct a corpus analysis of an open-source dataset to gain insights into the origin of how loneliness was expressed in Arabic on Twitter during the initial months of COVID-19 regulations and explored temporal trends to enhance comprehension of the prevalence of loneliness and mental health struggles during the initial months of the pandemic.",
keywords = "Arabic, Corpus Analysis, Covid-19, Loneliness, Thematic Analysis, Twitter",
author = "Chereen Shurafa and Wajdi Zaghouani",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 8th International Conference on Arabic Language Processing, ICALP 2023 ; Conference date: 19-04-2024 Through 20-04-2024",
year = "2025",
month = feb,
doi = "10.1007/978-3-031-80438-0\_7",
language = "English",
isbn = "9783031804373",
volume = "2340",
series = "Communications In Computer And Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "80--93",
editor = "B Hdioud and SL Aouragh",
booktitle = "Arabic Language Processing: From Theory To Practice, Icalp 2023, Pt Ii",
address = "Germany",
}