scholarly journals #BoomerRemover: COVID-19, Ageism, and the Intergenerational Twitter Response

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 931-931
Author(s):  
Antonius Skipper ◽  
Daniel Rose
Keyword(s):  
Older Adults ◽  
Baby Boomers ◽  
Older Men ◽  
Social Media Platform ◽  
The Social ◽  
The World ◽  
Open Coding ◽  
Media Platform ◽  
Twitter Users ◽  
News Headlines

Abstract In March 2020, COVID-19 was declared a pandemic and frequently presented as a virus primarily affecting older adults. News headlines led with statements such as, “Coronavirus deaths are so far mostly older men” (Ramzy, 2020). Although later determined inaccurate, this perspective contributed to openly ageist views and exchanges from people around the world. On the social media platform of Twitter, #BoomerRemover was used as a hashtag to express views related to older adults, and particularly baby boomers, as the primary targets of COVID-19. This study uses qualitative methods to analyze the messages of Twitter users that discuss COVID-19 with the use of the hashtag #BoomerRemover. A total of 1,875 tweets posted in English and including the hashtag “#BoomerRemover” from March 16, 2020 to March 30, 2020 were analyzed. Analytic methods employed an open coding procedure consistent with grounded theory and Numeric Content Analysis (Marks, 2015). Salient themes include: (1) COVID-19 is Politically Driven (2) There’s a Real Intergenerational Divide, (3) Young People are Dying Too, and (4) #BoomerRemover is Simply Disrespectful. Findings suggest that only about a fourth of #BoomerRemover tweets could be considered ageist, and the large majority of tweets using the hashtag were related to politics and elections. Further, several of those using the #BoomerRemover hashtag to defend older adults were inadvertently causing it to remain relevant (trend) as a Twitter topic. This study recognizes the importance of considering Twitter – primarily composed of young adults – as a place where intergenerational attitudes vis-à-vis COVID-19 may be expressed.

scholarly journals Linguistic drivers of misinformation diffusion on social media during the COVID-19 pandemic

2021 ◽  
Author(s):  
Giandomenico Di Domenico ◽  
Annamaria Tuan ◽  
Marco Visentin
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
New Technologies ◽  
Fake News ◽  
Conspiracy Theories ◽  
Social Media Platform ◽  
The Social ◽  
Media Platform ◽  
Textual Cues ◽  
Twitter Users

AbstractIn the wake of the COVID-19 pandemic, unprecedent amounts of fake news and hoax spread on social media. In particular, conspiracy theories argued on the effect of specific new technologies like 5G and misinformation tarnished the reputation of brands like Huawei. Language plays a crucial role in understanding the motivational determinants of social media users in sharing misinformation, as people extract meaning from information based on their discursive resources and their skillset. In this paper, we analyze textual and non-textual cues from a panel of 4923 tweets containing the hashtags #5G and #Huawei during the first week of May 2020, when several countries were still adopting lockdown measures, to determine whether or not a tweet is retweeted and, if so, how much it is retweeted. Overall, through traditional logistic regression and machine learning, we found different effects of the textual and non-textual cues on the retweeting of a tweet and on its ability to accumulate retweets. In particular, the presence of misinformation plays an interesting role in spreading the tweet on the network. More importantly, the relative influence of the cues suggests that Twitter users actually read a tweet but not necessarily they understand or critically evaluate it before deciding to share it on the social media platform.

scholarly journals Listening to #2A: Applying a Qualitative Method to Twitter Dialogue

2020 ◽  
Author(s):  
Laura Smith ◽  
Laila Abdel-Salam ◽  
Molly Coyne ◽  
Courtney McVicar ◽  
Divya Robin ◽  
...  
Keyword(s):  
Qualitative Research ◽  
Presidential Election ◽  
Qualitative Method ◽  
Qualitative Methodology ◽  
Consensual Qualitative Research ◽  
Social Media Platform ◽  
Second Amendment ◽  
The Social ◽  
Media Platform ◽  
Twitter Users

In this article, we present a project that explored the application of an established qualitative methodology to a novel source of data: microblog postings on the social media platform Twitter, also known as tweets. In particular, we adapted Consensual Qualitative Research (CQR; Hill, Thompson, & Williams, 1997) for use in this analysis. The coinciding aim of the project was to study the cultural impasses that seemed to characterize U.S. society surrounding the 2016 presidential election. Publicly available tweets bearing the hashtag #2A were selected for examination; this hashtag indicated the user’s intention to direct the posting to the attention of Twitter users in the context of the Second Amendment, which refers to citizens’ right to bear arms. The article describes the process by which CQR was modified for this use, profiles the exploratory findings, and present suggestions for subsequent similar research undertakings.

scholarly journals Social network analysis of climate change discussion on Twitter during COP21

2021 ◽  
Author(s):  
Brittany E. Harris
Keyword(s):  
Climate Change ◽  
Social Media ◽  
Social Network ◽  
Network Analysis ◽  
Social Media Platform ◽  
The Public ◽  
Climate Change Information ◽  
The Social ◽  
Media Platform ◽  
Twitter Users

The public is increasingly relying on Twitter for climate change information; however, to date, this social media platform is poorly understood in terms of how climate change information is shared. This study evaluates discussions on Twitter during the 2015 United Nations Conference on Climate Change (COP21) to elucidate the social media platform’s role in communicating climate change information. For a five-day period, links embedded in a sample of tweets containing “#climatechange” were characterized, Twitter users were classified by the types of links they typically shared, and their degree centralities (the number of connections for each user) were measured. There was little skeptical content across all user categories; however, news links were more likely than non-news to contain content that is skeptical of climate change. Users who typically shared skeptical news links and users who typically shared non-skeptical non-news links exhibited a relatively high number of connections with other users.

scholarly journals Personal Branding through Da'wah on TikTok Social Media

2021 ◽  
Vol 3 (1) ◽  
pp. 85-94
Author(s):  
Amirah Nabilah ◽  
Bhunga Aulia ◽  
Dwi Yuniar
Keyword(s):  
Social Media ◽  
Research Team ◽  
Qualitative Approach ◽  
Descriptive Data ◽  
Collection Method ◽  
Social Media Platform ◽  
The Social ◽  
The World ◽  
Media Platform ◽  
Personal Branding

The COVID-19 pandemic that has hit the world requires people to stay at home, making social media the choice of people to seek entertainment or share knowledge. TikTok is one of the interesting centers for preachers to do their preaching. This study discussed Personal Branding on Husain Basyaiban @basyasman00 account through TikTok social media intending to be achieved by researchers is to find out how personal branding Husain Basyaiban through three da'wah content with the highest viewers on social media TikTok. Husain is a person with successful personal branding through the social media networking platform TikTok, where he presents content about Islamic Da'wah. Based on this, the research team was interested in analyzing how the personal branding process carried out by Husain Basyaiban through Da'wah on the social media platform TikTok. This research uses a qualitative approach with a data collection method in the form of document study, resulting in descriptive data in the form of written words from the behavior studied. The results of the research showed that Husain Basyaiban can meet 11 Criteria for Effective Authentic Personal Branding, namely Authenticity, Integrity, Consistency, Specialization, Authority, Privileges, Relevant, Perseverance, Visibility, Good Deeds, Performance.

scholarly journals Crowdfunding Salafism Crowdfunding as a Salafi Missionising Method

Religions ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 209
Author(s):  
Simon Sorgenfrei
Keyword(s):  
Social Media ◽  
Young People ◽  
Social Media Platform ◽  
Consumer Value ◽  
Online Presence ◽  
The Social ◽  
The World ◽  
Outreach Programme ◽  
Media Platform ◽  
New Perspective

As is also the case in other parts of the world, Salafi interpretations of Islam appear to be on the rise in Sweden, especially among young people turning to Islam. One of the most active and visible missionising Salafi organisations in Sweden is called islam.nu. It is based in Stockholm but has a national outreach programme and a very active online presence. This article focuses on islam.nu and a dawa campaign called #karavanen (the Caravan) and how it was advertised and developed on the social media platform Instagram from March 2018 to March 2020. By using market and consumer value theories to analyse the Instagram content related to the #karavanen, the article is an explorative attempt to approach contemporary Salafi missionising and growth from a new perspective.

Study on Dengue Cases

2019 ◽  
Vol 1 (2) ◽  
pp. 101-105
Author(s):  
Nur Amiratun Nazihah Roslan ◽  
Hairulnizam Mahdin ◽  
Shahreen Kasim
Keyword(s):  
Social Networking ◽  
Data Availability ◽  
Social Media Platform ◽  
Data Mining Tool ◽  
Huge Data ◽  
Technology Advancement ◽  
The Social ◽  
The World ◽  
Media Platform ◽  
Mining Tool

With the rise of social networking approach, there has been a surge of users generated content all over the world and with that in an era where technology advancement are up to the level where it could put us in a step ahead of pathogens and germination of diseases, we couldn’t help but to take advantage of that advancement and provide an early precaution measures to overcome it. Twitter on the other hand are one of the social media platform that provides access towards a huge data availability. To manipulate those data and transform it into an important information that could be used in many different scope that could help improve people’s life for the better. In this paper, we gather three different algorithm from Lazy classifier to compare between them on which algorithm suited the most with the dengue fever dataset. This research are using WEKA as the data mining tool for data analyzation.

Analysing Sentiment Analysis Twitter Data On Dengue Cases by Using Bayes Classification

2019 ◽  
Vol 1 (2) ◽  
pp. 91-95
Author(s):  
Nur Amiratun Nazihah Roslan ◽  
Hairulnizam Mahdin ◽  
Shahreen Kasim
Keyword(s):  
Social Networking ◽  
The Other ◽  
Bayes Classifier ◽  
Social Media Platform ◽  
Data Mining Tool ◽  
Twitter Data ◽  
The Social ◽  
The World ◽  
Media Platform ◽  
Mining Tool

With the rise of social networking approach, there has been a surge ofusers generated content all over the world and with that in an era wheretechnology advancement are up to the level where it could put us in astep ahead of pathogens and germination of diseases, we couldn’t helpbut to take advantage of that advancement and provide an earlyprecaution measures to overcome it. Twitter on the other hand are oneof the social media platform that provides access towards a huge dataavailability. To manipulate those data and transform it into an importantinformation that could be used in many different scope that could helpimprove people’s life for the better. In this paper, we gather fourdifferent algorithm from Bayes classifier to compare between them onwhich algorithm suited the most with the dengue fever dataset. Thisresearch are using WEKA and also Eclipse as the data mining tool fordata analyzation.

scholarly journals Social network analysis of climate change discussion on Twitter during COP21

2021 ◽  
Author(s):  
Brittany E. Harris
Keyword(s):  
Climate Change ◽  
Social Media ◽  
Social Network ◽  
Network Analysis ◽  
Social Media Platform ◽  
The Public ◽  
Climate Change Information ◽  
The Social ◽  
Media Platform ◽  
Twitter Users

The public is increasingly relying on Twitter for climate change information; however, to date, this social media platform is poorly understood in terms of how climate change information is shared. This study evaluates discussions on Twitter during the 2015 United Nations Conference on Climate Change (COP21) to elucidate the social media platform’s role in communicating climate change information. For a five-day period, links embedded in a sample of tweets containing “#climatechange” were characterized, Twitter users were classified by the types of links they typically shared, and their degree centralities (the number of connections for each user) were measured. There was little skeptical content across all user categories; however, news links were more likely than non-news to contain content that is skeptical of climate change. Users who typically shared skeptical news links and users who typically shared non-skeptical non-news links exhibited a relatively high number of connections with other users.

scholarly journals A Study on Dengue Cases Detection based on Lazy Classifier

2019 ◽  
Vol 1 (1) ◽  
pp. 43-47
Author(s):  
Nur Amiratun Nazihah Roslan ◽  
Hairulnizam Mahdin ◽  
Shahreen Kasim
Keyword(s):  
Social Networking ◽  
Data Availability ◽  
Social Media Platform ◽  
Data Mining Tool ◽  
Huge Data ◽  
Technology Advancement ◽  
The Social ◽  
The World ◽  
Media Platform ◽  
Mining Tool

With the rise of social networking approach, there has been a surge of users generated content all over the world and with that in an era where technology advancement are up to the level where it could put us in a step ahead of pathogens and germination of diseases, we couldn’t help but to take advantage of that advancement and provide an early precaution measures to overcome it. Twitter on the other hand are one of the social media platform that provides access to a huge data availability. To manipulate those data and transform it into an important information that could be used in many different scopes that could help improve people’s lives for the better. In this paper, we gather a total of six algorithms from Lazy Classifier to compare between them on which algorithm suited the most with the diabetes dataset. This research are using WEKA as the data mining tool for data analyzation 

Performance Comparison among Meta Classifier Algorithms in WEKA

2019 ◽  
Vol 1 (2) ◽  
pp. 106-112
Author(s):  
Nur Amiratun Nazihah Roslan ◽  
Hairulnizam Mahdin ◽  
Shahreen Kasim
Keyword(s):  
Social Networking ◽  
Performance Comparison ◽  
Data Availability ◽  
Data Mining Tool ◽  
Huge Data ◽  
Technology Advancement ◽  
The Social ◽  
The World ◽  
Media Platform ◽  
Mining Tool

With the rise of social networking approach, there has been a surge of users generated content all over the world and with that in an era where technology advancement are up to the level where it could put us in a step ahead of pathogens and germination of diseases, we couldn’t help but to take advantage of that advancement and provide an early precaution measures to overcome it. Twitter on the other hand are one of the social media platform that provides access towards a huge data availability. To manipulate those data and transform it into an important information that could be used in many different scope that could help improve people’s life for the better. In this paper, we gather all algorithm that are available inside Meta Classifier to compare between them on which algorithm suited the most with the dengue fever dataset. This research are using WEKA as the data mining tool for data analyzation.

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