Identifying Cues to Deception in Islamic Websites Text-Based Content and Design

Mohamed, Fatima Ahmed; Aziz, Madihah Sheikh Abdul; Zulkifli, Zahidah; Mahmud, Murni

doi:10.1109/ict4m.2018.00059

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…As an example, Facebook pages were used by a Danish right-wing party to spread hate and fake news against Muslims [28]. The other motive is that these pages may belong to groups claiming to be affiliated with Islam, but they publish deceptive content by spreading distorted Qur'anic verses, wrong interpretations, or using negative emotions, to show a bad impression of Islam [33]. In addition, among these motives, some of these pages belong to extremist groups that carry extremist ideologies that contradict the tolerant teachings of Islam or adopt ideas stemming from a wrong interpretation of the rulings of Islam, to brainwash people who do not have prior knowledge of the Islamic religion and its noble principles to attract them to implement their goals by claiming that they are applying God's law [28].…”

Section: Spread Of Disinformation About Islammentioning

confidence: 99%

Disinformation Detection About Islamic Issues on Social Media Using Deep Learning Techniques

Kh. Hamed,

Ab Aziz,

Yaakub

2023

MJCS

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Nowadays, many people receive news and information about what is happening around them from social media networks. These social media platforms are available free of charge and allow anyone to post news or information or express their opinion without any restrictions or verification, thus contributing to the dissemination of disinformation. Recently, disinformation about Islam has spread through pages and groups on social media dedicated to attacking the Islamic religion. Many studies have provided models for detecting fake news or misleading information in many domains, such as political, social, economic, and medical, except in the Islamic domain. Due to this negative impact of spreading disinformation targeting the Islamic religion, there is an increase in Islamophobia, which threatens societal peace. In this paper, we present a Bidirectional Long Short-Term Memory-based model trained on an Islamic dataset (RIDI) that was collected and labeled by two separate specialized groups. In addition, using a pre-trained word-embedding model will generate Out-Of-Vocabulary, because it deals with a specific domain. To address this issue, we have retrained the pre-trained Glove model on Islamic documents using the Mittens method. The results of the experiments proved that our proposed model based on Bidirectional Long Short-Term Memory with the retrained Glove model on the Islamic articles is efficient in dealing with text sequences better than unidirectional models and provides a detection accuracy of 95.42% of Area under the ROC Curve measure compared to the other models.

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Section: Spread Of Disinformation About Islammentioning

confidence: 99%

Disinformation Detection About Islamic Issues on Social Media Using Deep Learning Techniques

Kh. Hamed,

Ab Aziz,

Yaakub

2023

MJCS

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“…Kajian literatur menunjukkan kajian yang terhad mengenai indikator kewibawaan maklumat di media sosial dalam perspektif Islam. Menurut Wan-Chik (2013) dan Mohamed et al (2018), terdapat keperluan yang kritikal untuk membuat kajian lanjut bagi mengenal pasti lebih banyak indikator kewibawaan maklumat Islam. Beberapa kajian dalam domain teknologi Islam telah cuba mengkaji kesan indikator kewibawaan mesej Islam atas talian yang kebanyakannya disiarkan melalui laman Web Islam.…”

Section: Permasalahan Kajianunclassified

Indikator Kewibawaan Maklumat Islam di Media Sosial Melalui Kesepakatan Pakar (Indicators on Social Media Islamic Information Credibility through an Expert Agreement)

Kadir¹,

Judi²

2019

JKMJC

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Media sosial merupakan alat penting dalam perkongsian maklumat yang dapat menyebar maklumat dengan segera berbanding media arus perdana tradisional. Sarjana Islam juga menggunakan media sosial bagi tujuan dakwah untuk mendekati belia khususnya kerana sifat mereka yang celik digital. Namun, sesetengah maklumat sukar ditentukan kebenarannya, sengaja direka untuk mencetus perbalahan atau sengaja ditular untuk menyokong sentimen. Maklumat Islam yang tidak tepat dikhuatiri merosakkan akidah belia muslim yang kurang matang dan banyak bergantung kepada media sosial untuk mencari sumber maklumat yang diperlukan. Kajian empirikal berkaitan dengan indikator kewibawaan maklumat Islam di media sosial yang sah adalah terhad. Objektif kajian adalah untuk mengenal pasti dan mengesahkan dimensi dan indikator kewibawaan maklumat Islam di media sosial. Kajian menggunakan kaedah perbincangan kumpulan fokus sebagai sebahagian daripada proses pengesahan dalam fasa reka bentuk dan pembangunan, metod Fuzzy Delphi (FDM). Data kumpulan fokus yang dilanjutkan dengan soal selidik terhadap 15 panel pakar digunakan untuk menilai dan mengesah definisi indikator kewibawaan maklumat Islam. Keputusan menunjukkan kebanyakan pengguna bersetuju indikator autoriti dan sumber penulisan berdasar Al-Quran dan hadis sahih adalah rujukan utama dalam menilai kandungan maklumat Islam. Pengguna tidak hanya memproses maklumat secara sistematik, tetapi juga mengambil kira ciri kandungan maklumat dan pengaruh sosial rangkaian terdekat apabila menilai kewibawaan maklumat dalam talian. Hasil kajian adalah indikator kewibawaan maklumat yang sah yang dapat membantu pengguna media sosial terutama belia muslim untuk menentukan kesahihan dan sumber maklumat Islam di media sosial. Kajian dimanfaat bagi mencadangkan beberapa cara untuk menjalankan penyelidikan dan penilaian kewibawaan maklumat Islam dalam talian.

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“…Fake or misleading information regarding religious issues can influence people's beliefs, attitudes, intentions, motivations, or behaviour. It can distort the true Islamic teachings, especially for new Muslims and the younger generation [2]. Islamic websites are very useful for new Muslims and non-Muslims who want to understand Islam in a simple and systematic way.…”

Section: Introductionmentioning

confidence: 99%

“…It could be difficult to define truth in the context of Islamic websites because there are many different schools of thought regarding Islamic practices [4]. As a result, the teachings of Islam for new Muslims and the younger generation can be altered [2]. The main branches within Islam are Sunnah and Shia.…”

Section: Introductionmentioning

confidence: 99%

Classifying Muslim Ideologies from Islamic Websites using Text Analysis Based on Naive Bayes and TF-IDF

Olowolayemo,

Moustafa Sharey Moustafa

2024

IJPCC

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Reliable digital Islamic information is one of the challenges faced by innocent Islamic information seekers such as young Muslims, new Muslims as well as others who desire to find authentic information about Islam, Prophet Muhammad (saw), and Muslims, in general. Several deviant ideologies abound, and they also present their information using the internet, sometimes involving digital deception. In the digital era, misleading Islamic information may affect people’s beliefs, behaviours, and attitudes. Many websites are equally based on several schools of thought regarding Islamic practices which could be difficult for the new Muslims, and the young generation of Muslims to recognize what to follow among these different websites based on the information presented on the sites. Some other variants of practices are considered to be deviants by the mainstream Sunni scholars which may be misleading for innocent Islamic information seekers including non-Muslims. Consequently, the need to categorize different Islamic websites based on different schools and branches becomes imperative. This initial study focuses classification of Islamic websites utilising website categorization and text classification approach to their textual contents. The proposed technique classified 60 Islamic websites into two various categories Sunni and Shia using TF-IDF for features extraction while using Multinomial Naive Bayes for classification. In addition, extracting the keywords for each of the two categories assisted in the classification process. The results show that Multinomial Naive Bayes was easily implemented and predicted the categories of Islamic websites with an accuracy of 0.89, precision 1.0, recall 0.80, as well as an F1 score of 0.89. The keywords that differentiate Sunni websites from Shia's websites were extracted. It was found that the best keywords that can be used in search engines to identify Sunni websites are Islam and Muslim, while Shia and Imam are the most prominent keywords that can be used to identify Shia's websites.

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Identifying Cues to Deception in Islamic Websites Text-Based Content and Design

Abstract: Web of Science [v.5.32]-Web of Science Core Collection Full Record apps.webofknowledge.com.ezproxy.um.edu.my/full_record.do?product=WOS&search_mode=GeneralSearch&qid=5&SID=F5fKSTykDhJTaHPL793&p… 1/4

Cited by 4 publications

References 13 publications

Disinformation Detection About Islamic Issues on Social Media Using Deep Learning Techniques

Disinformation Detection About Islamic Issues on Social Media Using Deep Learning Techniques

Indikator Kewibawaan Maklumat Islam di Media Sosial Melalui Kesepakatan Pakar (Indicators on Social Media Islamic Information Credibility through an Expert Agreement)

Classifying Muslim Ideologies from Islamic Websites using Text Analysis Based on Naive Bayes and TF-IDF

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