scholarly journals The Anti-Social Network? Framing Social Media in Wartime

2018 ◽  
Vol 4 (3) ◽  
pp. 205630511880031 ◽  
Author(s):  
Azi Lev-On
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Social Network ◽  
Collective Action ◽  
Public Diplomacy ◽  
Hate Speech ◽  
Mainstream Media ◽  
Hebrew Language ◽  
Perceived Effects ◽  
Media Channels

Numerous studies address the uses and perceived effects of social media, but a scholarly void exists about how it is framed in the mainstream media. This study fills this void using a content analysis of news items that included references to social media in Israel’s six daily Hebrew-language printed newspapers during the Israel–Gaza war (2014). The papers framed social media primarily as spaces of hate speech and distribution of rumors. Additional salient themes referred to social media as alternative media channels by politicians and celebrities and as arenas of public diplomacy. Social media was rarely portrayed as platforms to orchestrate collective action or to meet the enemy.

Young adults know that their issues are not represented in the news: Israeli young adults and mainstream news media

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Benny Nuriely ◽  
Moti Gigi ◽  
Yuval Gozansky
Keyword(s):  
Social Media ◽  
Young Adults ◽  
Content Analysis ◽  
Social Relations ◽  
News Media ◽  
Media Coverage ◽  
Online News ◽  
Content Type ◽  
Mainstream Media ◽  
The Media

Purpose This paper aims to analyze the ways socio-economic issues are represented in mainstream news media and how it is consumed, understood and interpreted by Israeli young adults (YAs). It examines how mainstream media uses neo-liberal discourse, and the ways YAs internalize this ethic, while simultaneously finding ways to overcome its limitations. Design/methodology/approach This was a mixed methods study. First, it undertook content analysis of the most popular Israeli mainstream news media among YAs: the online news site Ynet and the TV Channel 2 news. Second, the authors undertook semi-structured in-depth interviews with 29 Israeli YAs. The analysis is based on an online survey of 600 young Israelis, aged 18–35 years. Findings Most YAs did not perceive mainstream media as enabling a reliable understanding of the issues important to them. The content analysis revealed that self-representation of YAs is rare, and that their issues were explained, and even resolved, by older adults. Furthermore, most of YAs' problems in mainstream news media were presented using a neo-liberal perspective. Finally, from the interviews, the authors learned that YAs did not find information that could help them deal with their most pressing economic and social issue, in the content offered by mainstream media. For most of them, social media overcomes these shortcomings. Originality/value Contrary to research that has explored YAs’ consumerism of new media outlets, this article explores how YAs in Israel are constructed in the media, as well as the way in which YAs understand mainstream and new social media coverage of the issues most important to them. Using media content analysis and interviews, the authors found that Young Adults tend to be ambivalent toward media coverage. They understand the lack of media information: most of them know that they do not learn enough from the media. This acknowledgment accompanies their tendency to internalize the neo-liberal logic and conservative Israeli national culture, in which class and economic redistribution are largely overlooked. Mainstream news media uses neo-liberal discourse, and young adults internalize this logic, while simultaneously finding ways to overcome the limitations this discourse offers. They do so by turning to social media, mainly Facebook. Consequently, their behavior maintains the logic of the market, while also developing new social relations, enabled by social media.

Nature of Tweets in the 2015 Nigerian Presidential Elections

2015 ◽  
Vol 2 (2) ◽  
pp. 34-52 ◽  
Author(s):  
Nwachukwu Andrew Egbunike ◽  
Noel Ihebuzor ◽  
Ngozi Onyechi
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Presidential Election ◽  
Social Engagement ◽  
Presidential Elections ◽  
Hate Speech ◽  
Political Mobilization ◽  
Election Results

Social media is becoming increasingly important as a means for social engagement. In Nigeria, Twitter is employed to convey opinion and make commentary on matters ranging from football to politics. Tweets are also used to inform, advocate, recruit and even incite. Previous studies have shown that Twitter could be effective for political mobilization. However, there is dearth of research on how Twitter has been used as a purveyor of neutral and/or hate speech in the Nigerian context. This study examined the nature of tweets in the immediate aftermath of the 2015 presidential election in Nigeria. The authors employed content analysis of 250 purposively selected tweets from the #Igbo hashtag which trended between March 29 and 31, 2015. The tweets were then categorized into five explicit hate and one neutral tweet category respectively. Results revealed the dominance of three hate tweet types: derogatory, mocking and blaming. These findings were then discussed bearing in mind earlier theories on the functionality of tweets and voting patterns from an analysis of the election results.

Short Semantic Patterns: A Linguistic Pattern Mining Approach for Content Analysis Applied to Hate Speech

2020 ◽  
Vol 29 (02) ◽  
pp. 2040002
Author(s):  
Danielly Sorato ◽  
Fábio B. Goularte ◽  
Renato Fileto
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Pattern Mining ◽  
Hate Speech ◽  
Binary Classification ◽  
Word Embedding ◽  
Linguistic Patterns ◽  
Islamic Religion

Microblog posts such as tweets frequently contain users’ opinions and thoughts about events, products, people, institutions, etc. However, the usage of social media to prop-agate hate speech is not an uncommon occurrence. Analyzing hateful speech in social media is essential for understanding, fighting and discouraging such actions. We believe that by extracting fragments of text that are semantically similar it is possible to depict recurrent linguistic patterns in certain kinds of discourse. Therefore, we aim to use these patterns to encapsulate frequent statements textually expressed in microblog posts. In this paper, we propose to exploit such linguistic patterns in the context of hate speech. Through a technique that we call SSP (Short Semantic Pattern) mining, we are able to extract sequences of words that share a similar meaning in their word embedding representation. By analyzing the extracted patterns, we reveal some kinds of discourses that are replayed across a dataset, such as racist and sexist statements. Afterwards, we experiment using SSP as features to build classifiers that detect if a tweet contains hate speech (binary classification) and to distinguish between sexist, racist and clean tweets (ternary classification). The SSP instances encountered in tweets containing sexism have shown that a large number of sexist tweets began with the introduction ‘I’m not sexist but’ and ‘Call me sexist but’. Meanwhile, SSP instances found in tweets reproducing racism revealed a prominence of contents against the Islamic religion, associated entities and organizations.

Microfake: How small-scale deepfakes can undermine society

2020 ◽  
Vol 11 (2) ◽  
pp. 215-222 ◽  
Author(s):  
Tom Ascott
Keyword(s):  
Social Media ◽  
Small Scale ◽  
Local Elections ◽  
Democratic Institutions ◽  
Mainstream Media ◽  
Media Companies ◽  
Media Channels

Advances in deepfake technology have led to the emergence of a new picture of how doctored material will be used in disinformation campaigns. While safeguards ensure that manipulated videos may not be such a problem at the highest levels of security and defence, lower levels ‐ such as local elections ‐ remain vulnerable to malign actors. At such levels, deepfakes can be distributed using social media channels to target unsuspecting victims. Current solutions only protect individuals who are prominent enough to be covered by the mainstream media, and not enough is being done by governments or social media companies to protect ordinary users from coordinated inauthentic activity online. However, with more images and videos of ourselves online than ever before, anyone can be a victim of a disinformation campaign. As deepfakes become easier to make, no one is safe ‐ hyper-localized manipulation will create problems for democratic institutions that have not yet been fully understood.

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 Conative Meanings of Covid-19 Hate Speech on Social Media in the Perspective of Substantive Arguments

2020 ◽  
Vol 5 (4) ◽  
pp. 34-41
Author(s):  
Yuliana Setyaningsih
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Data Analysis ◽  
Hate Speech ◽  
Analysis Method ◽  
Basic Technique ◽  
Critical Awareness ◽  
Content Analysis Method ◽  
The Face ◽  
Analysis Design

This study aims to describe the results of the analysis of the conative meanings of Covid-19 hate speech on social media. The data of this study were excerpts from Covid-19 hate speech text on social media in March-May 2020. The data were collected by referring to the note taking technique as the basic technique. Data analysis were performed using the content analysis method. The design analysis method used was the estimated content analysis design. This design utilized all the knowledge researchers have in analyzing data about the conative meaning of Covid-19 hate speech. The results showed that Covid-19's hate speech had the following conative meanings: (1) insulting, (2) criticizing, (3) railing, (4) provoking, (5) harrasing, (6) blasheming, (7) insinuating, and (8) defaming. The results of this study are useful for building critical awareness of the community in the face of hate speech that is constantly present through social media in the community.

scholarly journals STRATEGIC INTELLIGENCE ANALYSIS OF RELIGION-BASED HATE SPEECH IN SOCIAL MEDIA: A CASE STUDY OF THE DIRECTORATE INTELLIGENCE AND SECURITY AT POLDA METRO JAYA

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Gilang Reno Prakoso ◽  
Arthur Josias Simon Runturambi
Keyword(s):  
Social Media ◽  
Media Coverage ◽  
Hate Speech ◽  
Active Role ◽  
Religious Communities ◽  
Intelligence Analysis ◽  
Religious Groups ◽  
Mainstream Media ◽  
Strategic Intelligence ◽  
Religious Intolerance

The development of communication technology continues to advance rapidly. Social media is able to present individual voices that have never been heard through mainstream media coverage before. In Indonesia, the changes in the world have become increasingly clear when the era of communication has flooded the lives of religious communities. Religious discourse in Indonesia in recent years has been colored by accusations of religious intolerance in the form of hate speech through social media. The prohibition on the construction of houses of worship, prohibition of book discussions, attacks on certain groups, heresy from certain religious groups, threatening expressions of hatred, and so on are a series of acts of religious intolerance so that the potential for social conflict appears clearly. The Police Intelligence and Security as an institution that has the obligation to carry out early detection of threats must play an active role in making prevention and anticipation efforts. This research examines the Strategic Intelligence Analysis of Religious-Based Hate Speech on Social Media by the Directorate of Intelligence and Security at Polda Metro Jaya.

scholarly journals Combatting hate and trolling with love and reason? A qualitative analysis of the discursive antagonisms between organized hate speech and counterspeech online

2020 ◽  
Vol 9 (4) ◽  
pp. 540-572
Author(s):  
Nadine Keller ◽  
Tina Askanius
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Hate Speech ◽  
Qualitative Content Analysis ◽  
Online Media ◽  
Moral Standards ◽  
Online Spaces ◽  
Media Practices ◽  
Good And Evil

An increasingly organized culture of hate is flourishing in today’s online spaces, posing a serious challenge for democratic societies. Our study seeks to unravel the workings of online hate on popular social media and assess the practices, potentialities, and limitations of organized counterspeech to stymie the spread of hate online. This article is based on a case study of an organized “troll army” of online hate speech in Germany, Reconquista Germanica, and the counterspeech initiative Reconquista Internet. Conducting a qualitative content analysis, we first unpack the strategies and stated intentions behind organized hate speech and counterspeech groups as articulated in their internal strategic documents. We then explore how and to what extent such strategies take shape in online media practices, focusing on the interplay between users spreading hate and users counterspeaking in the comment sections of German news articles on Facebook. The analysis draws on a multi-dimensional framework for studying social media engagement (Uldam & Kaun, 2019) with a focus on practices and discourses and turns to Mouffe’s (2005) concepts of political antagonism and agonism to operationalize and deepen the discursive dimension. The study shows that the interactions between the two opposing camps are highly moralized, reflecting a post-political antagonistic battle between “good” and “evil” and showing limited signs of the potentials of counterspeech to foster productive agonism. The empirical data indicates that despite the promising intentions of rule-guided counterspeech, the counter efforts identified and scrutinized in this study predominantly fail to adhere to civic and moral standards and thus only spur on the destructive dynamics of digital hate culture.

scholarly journals Flyktningengasjement i sosiale medier. Et mediepraksisperspektiv på flyktningsituasjonen i 2015

2018 ◽  
pp. 189-210
Author(s):  
Ivar Eimhjellen
Keyword(s):  
Social Media ◽  
Collective Action ◽  
Quantitative Study ◽  
Social Space ◽  
Voluntary Organizations ◽  
The Social ◽  
Social Media Engagement ◽  
Media Channels ◽  
Geographical Scope

This chapter is based on a quantitative study of Norwegians’ social media engagement for helping refugees in Norway in 2015, and how this was related to other acts and forms of help. I argue for and utilize a social and practice oriented media-perspective in which I conceptualize social media as practice and connected to other forms of practice in the social space. I find that social media, Facebook in particular, was part of disseminating attention and engagement for helping refugees rapidly all over Norway. As such, Facebook manifested itself as an infrastructure for the mobilization and organizing of volunteer contributions during the refugee situation. However, the scope of social media-assisted volunteer contributions was relatively small compared to the contributions through established voluntary organizations. Likewise, the established media-channels were also more important than social media for the spread of information on how to contribute. Based on this study, I claim that social media as an infrastructure for the mobilization and organizing of volunteer contributions serves a supplemental, albeit important function compared to established infrastructures. Social media supplement the established media and voluntary organizations by increasing the speed and geographical scope of mobilizing and organizing collective action.

scholarly journals Analyzing Social Media to Explore the Attitudes and Behaviors Following the Announcement of Successful COVID-19 Vaccine Trials: Infodemiology Study

10.2196/28800 ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. e28800
Author(s):  
Jean-Christophe Boucher ◽  
Kirsten Cornelson ◽  
Jamie L Benham ◽  
Madison M Fullerton ◽  
Theresa Tang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Content Analysis ◽  
Social Network ◽  
Multinational Corporations ◽  
Vaccine Hesitancy ◽  
Media Content ◽  
Media Content Analysis ◽  
Vaccine Trials ◽  
The Government

Background The rollout of COVID-19 vaccines has brought vaccine hesitancy to the forefront in managing this pandemic. COVID-19 vaccine hesitancy is fundamentally different from that of other vaccines due to the new technologies being used, rapid development, and widespread global distribution. Attitudes on vaccines are largely driven by online information, particularly information on social media. The first step toward influencing attitudes about immunization is understanding the current patterns of communication that characterize the immunization debate on social media platforms. Objective We aimed to evaluate societal attitudes, communication trends, and barriers to COVID-19 vaccine uptake through social media content analysis to inform communication strategies promoting vaccine acceptance. Methods Social network analysis (SNA) and unsupervised machine learning were used to characterize COVID-19 vaccine content on Twitter globally. Tweets published in English and French were collected through the Twitter application programming interface between November 19 and 26, 2020, just following the announcement of initial COVID-19 vaccine trials. SNA was used to identify social media clusters expressing mistrustful opinions on COVID-19 vaccination. Based on the SNA results, an unsupervised machine learning approach to natural language processing using a sentence-level algorithm transfer function to detect semantic textual similarity was performed in order to identify the main themes of vaccine hesitancy. Results The tweets (n=636,516) identified that the main themes driving the vaccine hesitancy conversation were concerns of safety, efficacy, and freedom, and mistrust in institutions (either the government or multinational corporations). A main theme was the safety and efficacy of mRNA technology and side effects. The conversation around efficacy was that vaccines were unlikely to completely rid the population of COVID-19, polymerase chain reaction testing is flawed, and there is no indication of long-term T-cell immunity for COVID-19. Nearly one-third (45,628/146,191, 31.2%) of the conversations on COVID-19 vaccine hesitancy clusters expressed concerns for freedom or mistrust of institutions (either the government or multinational corporations) and nearly a quarter (34,756/146,191, 23.8%) expressed criticism toward the government’s handling of the pandemic. Conclusions Social media content analysis combined with social network analysis provides insights into the themes of the vaccination conversation on Twitter. The themes of safety, efficacy, and trust in institutions will need to be considered, as targeted outreach programs and intervention strategies are deployed on Twitter to improve the uptake of COVID-19 vaccination.

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