Cancer Treatment Using Herbals in Arabic Social Media: Content Analysis of YouTube Videos

Author(s):  
Ajayeb S. Abu Daabes
2017 ◽  
Vol 6 (2) ◽  
pp. e19 ◽  
Author(s):  
Weizhou Tang ◽  
Kate Olscamp ◽  
Seul Ki Choi ◽  
Daniela B Friedman

2021 ◽  
Vol 13 (6) ◽  
pp. 3354
Author(s):  
Wei Sun ◽  
Shoulian Tang ◽  
Fang Liu

Destination image has been extensively studied in tourism and marketing, but the questions surrounding the discrepancy between the projected (perceptions from the National Tourism Organizations) and perceived destination image (perceptions from tourists) as well as how the discrepancy may influence sustainable experience remain unclear. Poor understanding of the discrepancy may cause tourist confusion and misuse of resources. The aim of this study is to empirically investigate if the perceived (by tourists) and projected (by NTOs) destination image are significantly different in both cognitive and affective aspects. Through a comprehensive social media content analysis of the NTO-generated and tourist-generated-contents (TGC), the current study identifies numerous gaps between the projected and perceived destination image, which offers some important theoretical and practical implications on destination management and marketing.


Author(s):  
Jing (Sasha) Jia ◽  
Nikki Mehran ◽  
Robert Purgert ◽  
Qiang (Ed) Zhang ◽  
Daniel Lee ◽  
...  

10.1142/10535 ◽  
2017 ◽  
Author(s):  
Kam-Fai Wong ◽  
Wei Gao ◽  
Ruifeng Xu ◽  
Wenjie Li

2019 ◽  
Vol 24 (4) ◽  
pp. 267-273
Author(s):  
Ajayeb S. Abu Daabes ◽  
Faten F. Kharbat

Purpose The purpose of this paper is to describe and assess Arabic videos related to cancer treatment to gain insights about the nature of health information as it is shared on YouTube. Accordingly, future strategies for different bodies are suggested to promote effective communication. Design/methodology/approach The approach is to select a representative sample of YouTube videos for certain search terms related to cancer treatment in the Arabic language. In order to identify the search terms, Google Trends is utilized. To retrieve the most relevant videos, a simple python tool is developed using YouTube API V3. For this study, the first 150 relevant videos are quantitatively and qualitatively analyzed. Objective data and subjective data are collected for each video and analyzed. Objective data include video title, URL, length, view count, like count, dislike count, comment count and the associated tags. For content analysis, coding themes are defined for the subjective data as follows: video format, video authorship and video content. Video content includes three categories: types of treatments, targeted part and evidence-based indicators. Findings The study included 150 videos, from which 30 videos were not content related; therefore, 120 videos remain in the analysis. Using rounding values, it can be observed that the average video lasted 10 min, had 184,966 views, was commented on 263 times, was liked by 2,295 users and disliked by 148 users. Non-professional individuals (46 percent) posted less than half of the videos, whereas public institutions posted only 18 percent of videos. More than half of videos (56 percent) promoted using herbal, botanical, and other natural products for cancer treatment. The majority of YouTube video formats were videos (52 percent), followed by audio with captions (30 percent). News and stories were the dominant videos, with (16 percent), and other types of videos were mostly testimonials and private centers promotions. Only 6 and 9 percent of videos targeted the genetic and immune systems, respectively. Out of the 120 analyzed videos, 86 percent did not mention any risk factor for the recommended treatment, and 73 percent did not offer the details of their usage direction. Research limitations/implications Researchers need to understand the information that is currently available on social media platforms related to the high-risk diseases in order to design initiatives, tools, and actions to allow an easy effective transfer of knowledge. Practical implications Recounting in-depth knowledge of YouTube cancer treatment contents will allow policy makers, YouTube management, medical organizations, and government agencies to understand the viewers’ behavior of YouTube and their needs to provide accurate and trustworthy information to adopt evidence-based resources. Social implications Creating the suitable content, in terms of health promotion strategies, associated with the appropriate format and understandable language that people need will be one of the major responsibilities of YouTube management, government and professional bodies. The well-designed health messages will enhance users’ engagement and attention to health issues from trusted sources. Originality/value There is very less information about Arabic messages in social media, YouTube in particular, specifically regarding cancer treatment. Thus, this study is one of the first studies to explore how Arabic messages are presented on YouTube. The aim of the assessment is to extract the current status and suggest future strategies for different bodies to have effective communication toward the Arabic communities.


2015 ◽  
Vol 27 (4) ◽  
pp. 1032-1044 ◽  
Author(s):  
Wayne Xin Zhao ◽  
Jinpeng Wang ◽  
Yulan He ◽  
Jian-Yun Nie ◽  
Ji-Rong Wen ◽  
...  

Author(s):  
Anna Karpova ◽  
Aleksey Savel'ev ◽  
Aleksandr Vil'nin ◽  
Anastasiya Kayda ◽  
Sergey Kuznecov ◽  
...  

The paper provides a brief review of current trends in studying ultra-right radicalization risks both in Russia and globally. Since the scientific interpretations in studying the notion of radicalization are differentiated, the authors prefer the following one: the ultra-rightists represent communities and movements that accept the idea that violence is necessary to achieve any goal (political, ideological, economic, social or personal). The ultra-rightists justify and promote this idea, expressing their willingness to act violently. They also make a moral commitment to defend those who promote the idea. The authors present the results of the work of the TPU’s cross-subject project team to create a prototype and a method for automated detection of ultra-rightists’ threats in social media. The paper describes the main challenges the researches face when applying smart social media content analysis as a tool for automating social science research.


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