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"وسائل التواصل الاجتماعي"
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Integrating Social Media Sentiment Analysis and Traditional Polling
This research explores the ongoing debate on whether social media sentiment analysis can replace traditional polling and advocates for the combined use of both methods to capture nuanced public perceptions expanding the geographic and linguistic scope of public opinion literature, this study focuses on Kuwait and the Arabic language. It examines public reactions to the Ministry of Higher Education's decision on June 9, 2023, to suspend scholarships for medical students at universities in Jordan and Egypt. The goal was to assess how data from both social media and traditional surveys can aid the government in understanding public opinion towards various policies. A significant contribution of this study is the development of the first multi-label emotion-classification tool specifically designed for Kuwaiti Arabic. This tool's unique capability to interpret and analyze the intricacies of the Kuwaiti dialect provided invaluable insights into local contexts and sentiments, setting a new benchmark for cultural and linguistic specificity in emotion-classification tools. The findings indicate that, while social media alone may not fully convey actual public opinion on political issues, adding survey data yields a richer, multi-dimensional perspective. This approach emphasizes the importance of integrating both methodologies to inform policymaking. The study further highlights the critical role of public opinion in shaping government policies and suggests that using both methods could lead to more informed decisions, enhance public trust, and reduce the likelihood of electoral sanctions.
Journal Article
Effects of Various Social Media on Users' Intercultural Communication Competence in Saudi Arabia
Intercultural communications have been transformed in recent years, largely due to the proliferation of social media applications. People from different countries and diverse cultures are now able to communicate with each other digitally, using multiple web-based communication platforms that have rapidly become an integral part of people's daily lives. Thus, the effects of social media use on the intercultural communication competence (ICC) of individuals has attracted the attention of many scholars. This study examines, in a Saudi Arabian context, the extent to which different social media applications affect users' ICC. The study is based on quantitative research methods, namely an online questionnaire to which 267 users responded. The study aims to explore participants' perceptions of the effects of different social media applications on their own ICC, taking into account various demographic factors such as the age, gender, and level of education attained by each participant. In addition, the study investigates which social media applications are most common in Saudi Arabia, and which have the greatest influence on users' ICC. The study's findings show that while WhatsApp is the most commonly used social media application in Saudi Arabia, Twitter is perceived to have the greatest effect on users' ICC.
Journal Article
معالم التنمر الإلكتروني في مواقع التواصل الإجتماعي
يسلط كتاب معالم التنمر الإلكتروني في مواقع التواصل الاجتماعي للدكتور محمد حسين أمين علي الضوء على ظاهرة متنامية في الفضاء الرقمي، حيث يستعرض أشكال التنمر الإلكتروني، ودوافعه النفسية والاجتماعية، وآثاره السلبية على الأفراد والمجتمعات. كما يناقش الكتاب الأطر القانونية والأخلاقية للتعامل مع هذه الظاهرة، ويقترح استراتيجيات وقائية وعلاجية للحد من انتشارها، مع التركيز على دور المؤسسات التربوية والإعلامية في التوعية وبناء ثقافة رقمية آمنة. ويعد هذا العمل مرجعا مهما للباحثين والمهتمين بقضايا الأمن السيبراني والسلوك الإنساني في البيئة الرقمية.
BOOK
TweetsentKw
Objectives: Arabic language is primarily represented in two varieties: Modern Standard Arabic (MSA) and Dialectal Arabic (DA). With the advent of social media, there has been a shift from the predominant use of MSA in writing to the incorporation of DA, thereby generating extensive resources for dialectal text studies. Kuwaiti Arabic (KA), a sub-variety of the Gulf dialect and one of the five principal Arabic dialects, differs significantly from MSA in all linguistic aspects. KA is an under- resourced language with a notable deficiency in language resources. The development of emotion classification tools relies heavily on the availability of resources such as annotated corpora. This study introduces TweetSentKW, a multi-label emotion annotated corpus for KA. Method: TweetSentKW was developed by collecting tweets and selecting relevant emotional classes for the annotation process. Each tweet was annotated by three independent annotators. Results: The TweetSentKW corpus comprises 40,000 manually labeled tweets across various topics. Besides constructing the corpus, this study provides a comprehensive analysis of annotator behavior and the co-occurrences of emotions. The corpus is anticipated to significantly contribute to sentiment analysis research, a crucial method for gauging public opinion. Conclusion: The widespread use of social media platforms, such as Twitter, has led to continuous and uninhibited public expression of opinions on diverse issues. The public and archived nature of these opinions presents a rich opportunity for researchers to analyze and understand public sentiment and perspectives.
Journal Article
The Reality and Prospects of Crowdfunding for Startups in the Digital Transformation Era
This research paper aims to investigate the role of crowdfunding models in assisting startup companies' fundraising efforts in the era of social media networks, electronic marketing, and digital transformation. This will be achieved through a comprehensive review of the literature, focusing on the evolution of digital transformation phases and the dynamics of startups in the application of crowdfunding platforms. This study assessed the global crowdfunding market at USD 19.86 billion in 2023. Startups account for 55 percent of this market. It is expected to expand from USD 22.12 billion at the end of 2024 to USD 72.88 billion by 2032, displaying a compound annual growth rate (CAGR) of 16.1% during the forecasting period (2024-2032).
Journal Article