scholarly journals Securitization of Islam and Muslims Through Social Media: A Content Analysis of Stopislam in Twitter

2020 ◽  
Vol V (IV) ◽  
pp. 186-203
Author(s):  
Raja Arslan Ahmad Khan ◽  
Mudassar Hussain Shah ◽  
Noor ul Bashar Ahmad
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Qualitative Analysis ◽  
Immigrants And Refugees ◽  
Sharia Law

The main objective of this paper is to examine the securitization of Islam and Muslims on Twitter. Therefore, whether and to what extent securitized images of Islam and Muslims have been produced on Twitter and to analyze the dominant securitized themes and their sub-dimensions. The methodology used for this purpose consisted of quantitative and qualitative analysis and analyzed hashtags #stopislam trending on Twitter. It was found that #stopislam produced securitized images of Islam and Muslims. Totalitarianism as a sub-dimension of ideological threat in the context of Securitization of Islam is dominating than Sharia Law and Jihadism while no evidence has been found in Whahabism Category. Similarly, in the existential threat category in the securitization of Muslims sub-dimension, general Muslims are dominating than Women's, immigrants and refugees on #stopislam. #stopislm produced less neutral and favoring Muslims Tweets evident that hashtag produced securitized images of Islam and Muslims.

scholarly journals What’s All the Chatter? A Mixed-Methods Analysis of Emergency Physicians’ Tweets

2019 ◽  
Vol 21 (1) ◽  
pp. 26-32 ◽  
Author(s):  
Jeff Riddell ◽  
Alisha Brown ◽  
Lynne Robins ◽  
Rafae Nauman ◽  
Jeanette Yang ◽  
...  
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Mixed Methods ◽  
Qualitative Analysis ◽  
Community Of Practice ◽  
Emergency Physicians ◽  
Shared Resources ◽  
Qualitative And Quantitative ◽  
Quantitative Analyses ◽  
Educational Delivery

Introduction: Twitter is growing in popularity and influence among emergency physicians (EP), with over 2200 self-identified EP users. As Twitter’s popularity has increased among EPs so too has its influence. While there has been debate about the value of Twitter as an effective educational delivery tool, little attention has been paid to the nature of the conversation occurring on Twitter. We aim to describe how influential EPs use Twitter by characterizing the language, purpose, frequencies, content, and degree of engagement of their tweets. Methods: We performed a mixed-methods analysis following a combined content analysis approach. We conducted qualitative and quantitative analyses of a sample of tweets from the 61 most influential EPs on Twitter. We present descriptive tweet characteristics and noteworthy themes. Results: We analyzed 1375 unique tweets from 57 unique users, representing 93% of the influential Twitter EPs. A majority of tweets (1104/1375, 80%) elicited some response in the form of retweets, likes, or replies, demonstrating community engagement. The qualitative analysis identified 15 distinct categories of tweets. Conclusion: Influential EPs on Twitter were engaged in largely medical conversations in which most messages generated some form of interaction. They shared resources and opinions while also building social rapport in a community of practice. This data can help EPs make informed decisions about social media engagement.

scholarly journals Data Mining and Content Analysis of the Chinese Social Media Platform Weibo During the Early COVID-19 Outbreak: Retrospective Observational Infoveillance Study

10.2196/18700 ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. e18700 ◽  
Author(s):  
Jiawei Li ◽  
Qing Xu ◽  
Raphael Cuomo ◽  
Vidya Purushothaman ◽  
Tim Mackey
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Quantitative Analysis ◽  
Qualitative Analysis ◽  
Hubei Province ◽  
Wuhan City ◽  
Social Media Data ◽  
Public Reaction ◽  
Media Data ◽  
Chinese Social Media

Background The coronavirus disease (COVID-19) pandemic, which began in Wuhan, China in December 2019, is rapidly spreading worldwide with over 1.9 million cases as of mid-April 2020. Infoveillance approaches using social media can help characterize disease distribution and public knowledge, attitudes, and behaviors critical to the early stages of an outbreak. Objective The aim of this study is to conduct a quantitative and qualitative assessment of Chinese social media posts originating in Wuhan City on the Chinese microblogging platform Weibo during the early stages of the COVID-19 outbreak. Methods Chinese-language messages from Wuhan were collected for 39 days between December 23, 2019, and January 30, 2020, on Weibo. For quantitative analysis, the total daily cases of COVID-19 in Wuhan were obtained from the Chinese National Health Commission, and a linear regression model was used to determine if Weibo COVID-19 posts were predictive of the number of cases reported. Qualitative content analysis and an inductive manual coding approach were used to identify parent classifications of news and user-generated COVID-19 topics. Results A total of 115,299 Weibo posts were collected during the study time frame consisting of an average of 2956 posts per day (minimum 0, maximum 13,587). Quantitative analysis found a positive correlation between the number of Weibo posts and the number of reported cases from Wuhan, with approximately 10 more COVID-19 cases per 40 social media posts (P<.001). This effect size was also larger than what was observed for the rest of China excluding Hubei Province (where Wuhan is the capital city) and held when comparing the number of Weibo posts to the incidence proportion of cases in Hubei Province. Qualitative analysis of 11,893 posts during the first 21 days of the study period with COVID-19-related posts uncovered four parent classifications including Weibo discussions about the causative agent of the disease, changing epidemiological characteristics of the outbreak, public reaction to outbreak control and response measures, and other topics. Generally, these themes also exhibited public uncertainty and changing knowledge and attitudes about COVID-19, including posts exhibiting both protective and higher-risk behaviors. Conclusions The results of this study provide initial insight into the origins of the COVID-19 outbreak based on quantitative and qualitative analysis of Chinese social media data at the initial epicenter in Wuhan City. Future studies should continue to explore the utility of social media data to predict COVID-19 disease severity, measure public reaction and behavior, and evaluate effectiveness of outbreak communication.

Character assassination as a right-wing populist communication tactic on social media: The case of Matteo Salvini in Italy

2021 ◽  
pp. 146144482110392
Author(s):  
Carlo Berti ◽  
Enzo Loner
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Qualitative Analysis ◽  
Communication Strategy ◽  
Right Wing ◽  
Media Communication ◽  
The People ◽  
Individual Traits ◽  
Social Media Communication

The article conceptualizes character assassination (CA) as a tactic of populist communication on social media by using the case study of Italian politician Matteo Salvini. CA consists of personal attacks aimed at damaging the reputation of individuals, used as political means to attack the “enemies of the people.” By means of CA, populists operate a shift from issues and arguments toward individual traits and behaviors. CA’s importance is linked to the features of social media communication (i.e. disintermediation, speed, virality, fragmentation, emotionality). The article uses content analysis of tweets, and qualitative analysis of relevant examples; it demonstrates the strategic nature of CA in Salvini’s communication and identifies five functions (i.e. polarizing, personalizing, symbolic, discriminating, emotional) of CA in right-wing populist communication. CA’s logic is unpacked, by showing how the delegitimization of individuals is used to reinforce a populist communication strategy. Potential implications and responses to CA are discussed.

scholarly journals Data Mining and Content Analysis of the Chinese Social Media Platform Weibo During the Early COVID-19 Outbreak: Retrospective Observational Infoveillance Study (Preprint)

2020 ◽  
Author(s):  
Jiawei Li ◽  
Qing Xu ◽  
Raphael Cuomo ◽  
Vidya Purushothaman ◽  
Tim Mackey
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Quantitative Analysis ◽  
Qualitative Analysis ◽  
Hubei Province ◽  
Wuhan City ◽  
Social Media Data ◽  
Public Reaction ◽  
Media Data ◽  
Chinese Social Media

BACKGROUND The coronavirus disease (COVID-19) pandemic, which began in Wuhan, China in December 2019, is rapidly spreading worldwide with over 1.9 million cases as of mid-April 2020. Infoveillance approaches using social media can help characterize disease distribution and public knowledge, attitudes, and behaviors critical to the early stages of an outbreak. OBJECTIVE The aim of this study is to conduct a quantitative and qualitative assessment of Chinese social media posts originating in Wuhan City on the Chinese microblogging platform Weibo during the early stages of the COVID-19 outbreak. METHODS Chinese-language messages from Wuhan were collected for 39 days between December 23, 2019, and January 30, 2020, on Weibo. For quantitative analysis, the total daily cases of COVID-19 in Wuhan were obtained from the Chinese National Health Commission, and a linear regression model was used to determine if Weibo COVID-19 posts were predictive of the number of cases reported. Qualitative content analysis and an inductive manual coding approach were used to identify parent classifications of news and user-generated COVID-19 topics. RESULTS A total of 115,299 Weibo posts were collected during the study time frame consisting of an average of 2956 posts per day (minimum 0, maximum 13,587). Quantitative analysis found a positive correlation between the number of Weibo posts and the number of reported cases from Wuhan, with approximately 10 more COVID-19 cases per 40 social media posts (<i>P</i>&lt;.001). This effect size was also larger than what was observed for the rest of China excluding Hubei Province (where Wuhan is the capital city) and held when comparing the number of Weibo posts to the incidence proportion of cases in Hubei Province. Qualitative analysis of 11,893 posts during the first 21 days of the study period with COVID-19-related posts uncovered four parent classifications including Weibo discussions about the causative agent of the disease, changing epidemiological characteristics of the outbreak, public reaction to outbreak control and response measures, and other topics. Generally, these themes also exhibited public uncertainty and changing knowledge and attitudes about COVID-19, including posts exhibiting both protective and higher-risk behaviors. CONCLUSIONS The results of this study provide initial insight into the origins of the COVID-19 outbreak based on quantitative and qualitative analysis of Chinese social media data at the initial epicenter in Wuhan City. Future studies should continue to explore the utility of social media data to predict COVID-19 disease severity, measure public reaction and behavior, and evaluate effectiveness of outbreak communication.

scholarly journals A comprehensive analysis of #Enuresis conversation on Twitter

2020 ◽  
Vol 14 (7) ◽  
Author(s):  
Justin Yu ◽  
Adithya Balasubramanian ◽  
Jonathan A. Gerber ◽  
Abhishek Seth
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Standard Deviation ◽  
Qualitative Analysis ◽  
Geographic Location ◽  
Comprehensive Analysis ◽  
Average Standard Deviation ◽  
Twitter Analytics ◽  
Twitter Activity ◽  
The U.S

Introduction: We sought to perform a quantitative and qualitative analysis of online Twitter discussion of enuresis using the hashtag #Enuresis. Methods: Symplur, a fee-based Twitter analytics service, was employed to aggregate and analyze Twitter activity, users, and content for #Enuresis, the official Twitter hashtag for enuresis, between June 2016 and November 2018. Twitter activity was analyzed using average tweets and new users per month. Users were classified based on geographic location, occupation, and organizational affiliation. Content analysis was performed by retrieving information about Twitter engagement metrics, including retweets, links, media, mentions, replies, and frequently used words and hashtags. Results: A total of 3133 tweets and 1555 users utilizing #Enuresis were identified between June 28, 2016 and November 28, 2018. The average ± standard deviation [SD] number of tweets using #Enuresis per month were not significantly different from 2016 through 2018 (p=0.292). The number of users increased from six to 1555 during the study period, but there was no statistically significant increase in number of new users per month (p=0.346). Physicians comprised 14% of the top 100 influencers followed by medical device organizations (13%). Popular hashtags in #Enuresis tweets were #Bedwetting, #PisEnLaCama, #schoolnurses, #helpingkids, #ninos, and #salud. Hyperlinks used in #Enuresis tweets included advocacy, academic, commercial, and other social media websites. Conclusions: Our analysis of #Enuresis demonstrates that the online Twitter discussion regarding enuresis is growing. These results indicate that enuresis has a global appeal and has especially gained traction in European countries, as well as in the U.S.

scholarly journals Nasionalisme Tenaga Kerja Indonesia (TKI) Di Malaysia dalam Narasi Media Sosial

2018 ◽  
Vol 1 (2) ◽  
pp. 159-179
Author(s):  
Ali Maksum ◽  
Surwandono Surwandono
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Focus Group ◽  
Qualitative Analysis ◽  
Focus Group Discussion ◽  
Migrant Workers ◽  
Group Discussion ◽  
Structured Interview ◽  
The Social ◽  
Media Narratives

This article discusses the nationalism sentiment among Indonesian migrant workers in Malaysia from the social media narratives. The aims of this article are (1) to examine the framing of nationalism among Indonesian migrant workers in Malaysia; (2) to understand the typology of nationalism among Indonesian migrant workers in Malaysia; and (3) to examine the influences factors behind the nasionalism among Indonesian migrant workers in Malaysia. This is qualitative analysis sumplemented by structured interview as well as focus group discussion (FGD). The systematic content analysis on some particular documents is also applied in this study.

Sosyal medyada Suriye’li sığınmacılara yönelik algı: bir sözlük değerlendirmesi

2017 ◽  
Vol 4 (2) ◽  
pp. 185-200 ◽  
Author(s):  
Servet Kardeş ◽  
Çağla Banko ◽  
Berrin Akman
Keyword(s):  
Qualitative Research ◽  
Social Media ◽  
Content Analysis ◽  
Syrian Refugees ◽  
Analysis Method ◽  
Social Media Platform ◽  
Content Analysis Method ◽  
Negative News ◽  
Media Platform ◽  
Made In

Bu araştırmada sığınmacılara yönelik paylaşımların yapıldığı sosyal medyada yer alan sözlüklerden birinde sığınmacılara yönelik algıya bakılmıştır. Yöntem olarak nitel desende olan bu çalışmada, bir sosyal medya sitesinde yer alan paylaşımlar içerik analizi yoluyla derinlemesine incelenip yorumlanmıştır. Araştırmanın sonucunda sosyal medya kullanıcılarının sığınmacıları büyük bir güvensizlik ortamı ve huzursuzluk yaratan bireyler olarak gördükleri saptanmış, sığınmacılarla yaşanan deneyimlerin ve medyadaki haberlerin bu düşüncelerin oluşmasında etkisinin olduğu belirlenmiştir. Bunun yanında sosyal medya kullanıcılarının devletin sığınmacılar konusunda yanlış politika izlediğini düşündükleri ve sığınmacılar için etkili bir planlama yapılmadığını ifade ettikleri görülmüştür. Çalışmanın sonuçları doğrultusunda medyada sığınmacılar hakkında çıkan haberlerde olumsuz ve şiddet temalı haberlerin azaltılması, Suriyeli sığınmacıların durumu, sahip oldukları haklar ve topluma yansımaları hakkında doğru ve bilgilendirici kamu spotları hazırlanması ayrıca sığınmacıların topluma entegre olma sürecinin her basamağında daha planlı ve etkili bir yol izlenmesi önerilebilir.ABSTRACT IN ENGLISHPerceptions about Syrian refugees on social media: an evaluation of a social media platformIn this research, posts which are about Syrian refugees were published in a social media platform, called as “sözlük” were investigated. The research is a qualitative research. The posts in this platform are analyzed with content analysis method. According to results of analyses, social media users see Syrian refugees as people who create an insecure and a restless environment. The experiences people had with them and news have an effect on this view. In addition, social media users think that government made inappropriate policies and ineffective plans about Syrian refugees. It is suggested negative news about Syrian refugees should be decreased and government should make safer policies. In addition, adaptation of refugees to society should be made in more planned and effective way.

INSTAGRAM SEBAGAI SOCIAL MEDIA MARKETING DALAM MEMBANGUN BRAND AWARENESS FAKULTAS EKONOMI DAN BISNIS ISLAM

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Oktaria Ardika Putri
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Qualitative Analysis ◽  
Educational Institution ◽  
Social Media Marketing ◽  
Brand Awareness ◽  
Educational Institutions ◽  
Business People ◽  
Marketing Tool

Instagram is a social media application that is currently very popular in the community, especially among artist, politicians, and business people. Companies or advanced business must quicly adapt to the advancement of information technology in the form of social media as a marketing tool. Instagram social media also necessary to developing educational institutions. One of the educational institution that ae currently developing is the newly established Faculty of Economics and Business Islam (FEBI) at the Kediri State Islamic Institute (IAIN Kediri). This writing aims to examine the importance of Instagram as social media marketing to building FEBI IAIN Kediri Brand Awareness. Instagram social media is considered more effectives to embrace students and the community, so it is expected to facilitate marketing and communication between FEBI IAIN Kediri with the students or other agencies. The method of this reasearch is a qualitative analysis which reference libraries are used as a basis. Keywods:  Instagam,  social media, Faculty of Economics and Business Islam, IAIN Kediri

Comparing Representation of Depression on Reddit and Twitter Social Media Platforms (Preprint)

2020 ◽  
Author(s):  
Ethan Kaji ◽  
Maggie Bushman
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Content Analysis ◽  
Relative Frequency ◽  
Social Activity ◽  
Social Media Platforms ◽  
Dsm Iv ◽  
Twitter Users

BACKGROUND Adolescents with depression often turn to social media to express their feelings, for support, and for educational purposes. Little is known about how Reddit, a forum-based platform, compares to Twitter, a newsfeed platform, when it comes to content surrounding depression. OBJECTIVE The purpose of this study is to identify differences between Reddit and Twitter concerning how depression is discussed and represented online. METHODS A content analysis of Reddit posts and Twitter posts, using r/depression and #depression, identified signs of depression using the DSM-IV criteria. Other youth-related topics, including School, Family, and Social Activity, and the presence of medical or promotional content were also coded for. Relative frequency of each code was then compared between platforms as well as the average DSM-IV score for each platform. RESULTS A total of 102 posts were included in this study, with 53 Reddit posts and 49 Twitter posts. Findings suggest that Reddit has more content with signs of depression with 92% than Twitter with 24%. 28.3% of Reddit posts included medical content compared to Twitter with 18.4%. 53.1% of Twitter posts had promotional content while Reddit posts didn’t contain promotional content. CONCLUSIONS Users with depression seem more willing to discuss their mental health on the subreddit r/depression than on Twitter. Twitter users also use #depression with a wider variety of topics, not all of which actually involve a case of depression.

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