scholarly journals Contentious politics and social media : a study of the networked publics in the Ayotzinapa twitter protests #PaseDeLista1al43

2018 ◽  
Author(s):  
◽  
Rocio Araceli Galarza Molina
Keyword(s):  
Social Media ◽  
Social Network ◽  
Contentious Politics ◽  
Symbiotic Relationship ◽  
Mixed Methods Approach ◽  
Twitter Data ◽  
The People ◽  
Twitter Users ◽  
The Relationship ◽  
Networked Publics

This study analyzed the networked public that was emergent on Twitter based on analysis of the use of the hashtag #PaseDelista1al43 to protest the disappearance of 43 students in Mexico in 2014. As social media have expanded, practitioners of contentious politics have utilized these media for manifesting their claims and organizing. These #PaseDeLista1al43 Twitter protests are explored as a form of performing contentious politics. To address this phenomenon, this project took a mixed methods approach, combining social network analysis and thematic and content analysis of Twitter data and interviews. A total of 3,616 tweets from five different moments in the first two years of the #PaseDeLista1al43 Twitter protests were collected to examine their content, who their authors are, as well as the relationship between the people in the networked public. Additionally, interviews (N = 14) with participants of the #PaseDeLista1al43 Twitter protests were conducted to delve into protesters' perspectives on the demonstration. Results help elucidate how Twitter can be used to practice contentious politics and thus constitutes another resource in the repertoire for performing contentious politics. Additionally, this study aligns with other research that has identified Twitter as a place for the formation and expression of counterpublics that seek to challenge hegemonic narratives. Moreover, the analyses in this study strengthen our understanding of processes of networked gatekeeping and networked framing that occur within a networked public on Twitter. Unlike traditional processes of gatekeeping and framing, networked processes are supported by a symbiotic relationship between elite and non-elite Twitter users. Moreover, frames prevalent in the protest not only concerned facts about the case but also denoted efforts of the protesters to position themselves in the story of the Ayotzinapa case.

scholarly journals Analisis Kesiapan Masyarakat Pada Penerapan Smart City di Sosial Media Menggunakan SNA

2021 ◽  
Vol 5 (1) ◽  
pp. 69-81
Author(s):  
M. Khairul Anam ◽  
Tri Putri Lestari ◽  
Latifah ◽  
Muhammad Bambang Firdaus ◽  
Sofiansyah Fadli
Keyword(s):  
Social Media ◽  
Social Network ◽  
Network Analysis ◽  
Social Interactions ◽  
Smart City ◽  
The People ◽  
Twitter Users ◽  
The Government ◽  
The Relationship

Smart People, which means smart city residents or people, not only refers to one's education but also the quality of social interactions that are formed. This Social Network Analysis (SNA) emphasizes the relationship between actors / users rather than the attributes of these actors. This analysis aims to see whether the people of Pekanbaru are ready to face changes to a Smart City. Pekanbaru is a civil city that will build a Smart City, with a concept that adopts 6 pillars, one of which is Smart People. There are 720,000 Twitter users in Pekanbaru City, while the people who actively interact are only 227 users or around 0.031%. Meanwhile, a city that can be said to be ready should be around 60-80% of active users who provide opinions or comments to the government of Pekanbaru City. From this research, it can be concluded that the people of Pekanbaru City are not ready to face Smart City Madani as seen from the interaction of the community on social media Twitter.

Tweeting #Ferguson: Mediatized fields and the new activist journalist

2017 ◽  
Vol 20 (7) ◽  
pp. 2252-2271 ◽  
Author(s):  
Stephen R Barnard
Keyword(s):  
Field Theory ◽  
Social Media ◽  
Content Analysis ◽  
Social Network ◽  
Network Analysis ◽  
Mixed Methods Approach ◽  
Twitter Users ◽  
Journalistic Field

As a hybrid, journo-activist space, tweeting #Ferguson quickly emerged as a way for activists and journalists to network and spread information. Using a mixed-methods approach combining digital ethnographic content analysis with social network analysis and link analysis, this study examines journalistic and activist uses of Twitter to identify changes in field relations and practices. Employing the lenses of field theory and mediatization, this study finds parity and divergence in the themes, frames, format, and discourse of journalist and activist Twitter practices. While the traditions of objective journalism and affective activism persist, notable exceptions occurred, especially following acts of police suppression. The networked communities of professional and activist Twitter users were overlapping and interactive, suggesting hybridity at the margins of the journalistic field. Given the hybridizing of journalistic and journo-activist practices, this case study examines the role of social media in efforts to report on and bolster social change.

What the fake? Assessing the extent of networked political spamming and bots in the propagation of #fakenews on Twitter

2019 ◽  
Vol 43 (1) ◽  
pp. 53-71 ◽  
Author(s):  
Ahmed Al-Rawi ◽  
Jacob Groshek ◽  
Li Zhang
Keyword(s):  
Social Media ◽  
Data Sets ◽  
Fake News ◽  
Content Type ◽  
Mainstream Media ◽  
News Discourse ◽  
Twitter Data ◽  
News Organizations ◽  
Twitter Users ◽  
One Year

PurposeThe purpose of this paper is to examine one of the largest data sets on the hashtag use of #fakenews that comprises over 14m tweets sent by more than 2.4m users.Design/methodology/approachTweets referencing the hashtag (#fakenews) were collected for a period of over one year from January 3 to May 7 of 2018. Bot detection tools were employed, and the most retweeted posts, most mentions and most hashtags as well as the top 50 most active users in terms of the frequency of their tweets were analyzed.FindingsThe majority of the top 50 Twitter users are more likely to be automated bots, while certain users’ posts like that are sent by President Donald Trump dominate the most retweeted posts that always associate mainstream media with fake news. The most used words and hashtags show that major news organizations are frequently referenced with a focus on CNN that is often mentioned in negative ways.Research limitations/implicationsThe research study is limited to the examination of Twitter data, while ethnographic methods like interviews or surveys are further needed to complement these findings. Though the data reported here do not prove direct effects, the implications of the research provide a vital framework for assessing and diagnosing the networked spammers and main actors that have been pivotal in shaping discourses around fake news on social media. These discourses, which are sometimes assisted by bots, can create a potential influence on audiences and their trust in mainstream media and understanding of what fake news is.Originality/valueThis paper offers results on one of the first empirical research studies on the propagation of fake news discourse on social media by shedding light on the most active Twitter users who discuss and mention the term “#fakenews” in connection to other news organizations, parties and related figures.

scholarly journals Study of Automotive Brands Popularity in Indonesia Using Twitter Data

2016 ◽  
Vol 3 (1) ◽  
pp. 23-33
Author(s):  
Stevent Efendi ◽  
Alva Erwin ◽  
Kho I Eng
Keyword(s):  
Social Media ◽  
Social Network ◽  
Sentiment Analysis ◽  
Automotive Industry ◽  
Real World ◽  
The Internet ◽  
Brand Preference ◽  
Twitter Data ◽  
Wide Range ◽  
Widespread Phenomenon

Social media has been a widespread phenomenon in the recent years. People shared a lot of thought in social media, and these data posted on the internet could be used for study and researches. As one of the fastest growing social network, Twitter is a particularly popular social media to be studied because it allows researchers to access their data. This research will look the correlation between Twitter chatter of a brand and the sales of brands in Indonesia. Factors such as sentiment and tweet rate are expected to be able to predict the popularity of a brand. Being one of the biggest industries in Indonesia, automotive industry is an interesting subject to study. A wide range of people buys vehicles, and even gather as communities based on their car or motorcycle brand preference. The Twitter results of sentiment analysis and tweet rate will be compared with real world sales results published by GAIKINDO and AISI.

Weak Ties and Value of a Network in the New Internet Economy

2017 ◽  
pp. 66-84 ◽  
Author(s):  
Davide Di Fatta ◽  
Roberto Musotto ◽  
Vittorio D'Aleo ◽  
Walter Vesperi ◽  
Giacomo Morabito ◽  
...  
Keyword(s):  
Social Media ◽  
Social Network ◽  
Virtual Network ◽  
The Internet ◽  
Rapid Rise ◽  
A Value ◽  
Internet Economy ◽  
The Relationship ◽  
Practical Implications ◽  
Scholarly Attention

The rapid rise in internet economy is reflected in increased scholarly attention on the topic, with researchers increasingly exploring the marketing approaches and strategies now available through social media. The network provides a value for companies, thus becomes essential acquire greater awareness to evaluate and quantify its value. What are practical implications for managers? Social network analysis is nowadays an essential tool for researchers: the aim of this chapter is to extend the internet economy research to network theories. Today, there are emerging observations on the global internet economy, but there is a big gap in literature indeed. At first, literature focused on people. Now, on digitalized information. Firms are connected in a virtual network and there are undefined distances in terms of space and time. Traditional methods of analysis are no more efficient: to analyze the relationship in the network society, we need a different paradigm to approach network issue.

scholarly journals COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data

10.2196/19458 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e19458 ◽  
Author(s):  
Wasim Ahmed ◽  
Josep Vidal-Alaball ◽  
Joseph Downing ◽  
Francesc López Seguí
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
United Kingdom ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Conspiracy Theory ◽  
Fake News ◽  
The United Kingdom ◽  
Twitter Data

Background Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. Objective The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. Methods This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph’s vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. Results Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. Conclusions The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.

scholarly journals The Moderating Role of Social Network Size on Social Media Use and Self-Esteem: An Evolutionary Mismatch Perspective

2021 ◽  
Vol 12 ◽  
Author(s):  
Amy J. Lim ◽  
Clement Lau ◽  
Norman P. Li
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Comparison ◽  
Media Use ◽  
Self Esteem ◽  
Network Size ◽  
Social Media Use ◽  
Evolutionary Mismatch ◽  
Social Network Size ◽  
The Relationship

Existing meta-analyses have shown that the relationship between social media use and self-esteem is negative, but at very small effect sizes, suggesting the presence of moderators that change the relationship between social media use and self-esteem. Employing principles from social comparison and evolutionary mismatch theories, we propose that the social network sizes one has on social media play a key role in the relationship between social media use and self-esteem. In our study (N = 123), we showed that social media use was negatively related to self-esteem, but only when their social network size was within an evolutionarily familiar level. Social media use was not related to self-esteem when people’s social networks were at evolutionarily novel sizes. The data supported both social comparison and evolutionary mismatch theories and elucidated the small effect size found for the relationship between social media use and self-esteem in current literature. More critically, the findings of this study highlight the need to consider evolutionarily novel stimuli that are present on social media to better understand the behaviors of people in this social environment.

scholarly journals Electronic Cigarette Users' Perspective on the COVID-19 Pandemic: Observational Study Using Twitter Data (Preprint)

2020 ◽  
Author(s):  
Yankun Gao ◽  
Zidian Xie ◽  
Dongmei Li
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Topic Modeling ◽  
Viral Infections ◽  
Application Programming Interface ◽  
Electronic Cigarette ◽  
Twitter Data ◽  
Social Media Platforms ◽  
Twitter Users ◽  
Public Health Practitioners

BACKGROUND Previous studies have shown that electronic cigarette (e-cigarette) users might be more vulnerable to COVID-19 infection and could develop more severe symptoms if they contract the disease owing to their impaired immune responses to viral infections. Social media platforms such as Twitter have been widely used by individuals worldwide to express their responses to the current COVID-19 pandemic. OBJECTIVE In this study, we aimed to examine the longitudinal changes in the attitudes of Twitter users who used e-cigarettes toward the COVID-19 pandemic, as well as compare differences in attitudes between e-cigarette users and nonusers based on Twitter data. METHODS The study dataset containing COVID-19–related Twitter posts (tweets) posted between March 5 and April 3, 2020, was collected using a Twitter streaming application programming interface with COVID-19–related keywords. Twitter users were classified into two groups: Ecig group, including users who did not have commercial accounts but posted e-cigarette–related tweets between May 2019 and August 2019, and non-Ecig group, including users who did not post any e-cigarette–related tweets. Sentiment analysis was performed to compare sentiment scores towards the COVID-19 pandemic between both groups and determine whether the sentiment expressed was positive, negative, or neutral. Topic modeling was performed to compare the main topics discussed between the groups. RESULTS The US COVID-19 dataset consisted of 4,500,248 COVID-19–related tweets collected from 187,399 unique Twitter users in the Ecig group and 11,479,773 COVID-19–related tweets collected from 2,511,659 unique Twitter users in the non-Ecig group. Sentiment analysis showed that Ecig group users had more negative sentiment scores than non-Ecig group users. Results from topic modeling indicated that Ecig group users had more concerns about deaths due to COVID-19, whereas non-Ecig group users cared more about the government’s responses to the COVID-19 pandemic. CONCLUSIONS Our findings show that Twitter users who tweeted about e-cigarettes had more concerns about the COVID-19 pandemic. These findings can inform public health practitioners to use social media platforms such as Twitter for timely monitoring of public responses to the COVID-19 pandemic and educating and encouraging current e-cigarette users to quit vaping to minimize the risks associated with COVID-19.

scholarly journals Analysing Discussions Around Rural Health on Twitter During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Wasim Ahmed ◽  
Josep Vidal-Alaball ◽  
Josep Maria Vilaseca Llobet
Keyword(s):  
Social Media ◽  
Social Network ◽  
Network Analysis ◽  
Rural Health ◽  
Language Processing ◽  
Rural Areas ◽  
Twitter Data ◽  
Public Views ◽  
Share Information ◽  
Insight Into

Individuals from rural areas are increasingly using social media as a means of communication, receiving information, or actively complaining of inequalities and injustices. This study captured 57 days’ worth of Twitter data from June to August 2021 related to rural health. The study utilised social network analysis and natural language processing to analyse the data. It was found that Twitter served as a fruitful platform to raise awareness of problems faced by those living in rural areas. Overall, Twitter was utilised in rural areas to express complaints, to debate, and share information. Twitter could be leveraged as a powerful social listening tool for individuals and organisations who want to gain insight into public views around rural health.

scholarly journals Identifying Social Media Influencers using Graph Analytics

2020 ◽  
Author(s):  
Pankti Joshi ◽  
Sabah Mohammed
Keyword(s):  
Social Media ◽  
Community Structure ◽  
Social Network ◽  
Network Analysis ◽  
Unstructured Data ◽  
Graph Analytics ◽  
Content Sharing ◽  
Twitter Data ◽  
Data Graph ◽  
Flow Of Information

<div>Social network analysis has been an essential topic</div><div>with broad content sharing from social media. Defining the</div><div>directed links in social media determine the flow of information and indicates the user’s influence. Due to the enormous data and unstructured nature of sharing information, there are several challenges caused while handling data. Graph Analytics proves to be an essential tool for addressing problems such as building networks from unstructured data, inferring information from the system, and analyzing the community structure of a network. The proposed approach aims to determine the influencers on Twitter data, based on the follower’s count as well as the retweet count. Several graph-based algorithms are implemented on the data collected to find the influencer as well as communities in the network.</div>

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