scholarly journals Infrastructure and the Post-Truth Era: is Trump Twitter’s Fault?

2019 ◽  
Vol 2 (1) ◽  
pp. 17-38 ◽  
Author(s):  
Martin Oliver
Keyword(s):  
Social Media ◽  
Theoretical Analysis ◽  
Science And Technology Studies ◽  
Public Discourse ◽  
Political Rhetoric ◽  
The Public ◽  
Social Media Platforms ◽  
The Relationship ◽  
Knowledge Claims ◽  
Infrastructure Studies

Abstract This paper explores the relationship between social media and political rhetoric. Social media platforms are frequently discussed in relation to ‘post-truth’ politics, but it is less clear exactly what their role is in these developments. Specifically, this paper focuses on Twitter as a case, exploring the kinds of rhetoric encouraged or discouraged on this platform. To do this, I will draw on work from infrastructure studies, an area of Science and Technology Studies; and in particular, on Ford and Wajcman’s analysis of the relationships between infrastructure, knowledge claims and politics on Wikipedia. This theoretical analysis will be supplemented with evidence from previous studies and in the public domain, to illustrate the points made. This analysis echoes wider doubts about the credibility of technologically deterministic accounts of technology’s relationship with society, but suggests however that while Twitter may not be the cause of shifts in public discourse, it is implicated in them, in that it both creates new norms for discourse and enables new forms of power and inequality to operate.

scholarly journals “These Women are Making a Statement Against Rape and yet the only Thing Y'All can Focus on is ‘Eww They're Naked’”: Exploring Rape Culture on Facebook in South Africa

Gender Issues ◽  
2020 ◽  
Author(s):  
Zaida Orth ◽  
Michelle Andipatin ◽  
Brian van Wyk
Keyword(s):  
Social Media ◽  
South African ◽  
Public Discourse ◽  
Public Health Problem ◽  
Victim Blaming ◽  
Rape Culture ◽  
The Public ◽  
Social Media Platforms ◽  
Aggressive Male ◽  
Public Reaction

Abstract Sexual assault on campuses has been identified as a pervasive public health problem. In April 2016, students across South African universities launched the #Endrapeculture campaign to express their frustration against university policies which served to perpetuate a rape culture. The use of hashtag activism during the protest served to spark online public debates and mobilize support for the protests. This article describes the public reactions to the South African #Endrapeculture protests on the Facebook social media platform. Data was collected through natural observations of comment threads on news articles and public posts on the student protests, and subjected to content analysis. The findings suggest that the #nakedprotest was successful in initiating public conversations concerning the issue of rape culture. However, the reactions towards the #nakedprotest were divided with some perpetuating a mainstream public discourse which perpetuates rape culture, and others (re)presenting a counter-public that challenged current dominant views about rape culture. Two related main themes emerged: Victim-blaming and Trivialising Rape Culture. Victim-blaming narratives emerged from the commenters and suggested that the protesters were increasing their chances of being sexually assaulted by marching topless. This discourse seems to perpetuate the notion of the aggressive male sexual desire and places the onus on women to protect themselves. Other commenters criticised the #nakedprotest method through demeaning comments which served to derail the conversation and trivialise the message behind the protest. The public reaction to the #nakedprotest demonstrated that rape culture is pervasive in society and continues to be re(produced) through discourse on social media platforms. However, social media also offers individuals the opportunity to draw from and participate in multiple counter-publics which challenge these mainstream rape culture discourses.

scholarly journals Towards Combating Pandemic-Related Misinformation in Social Media

2021 ◽  
pp. 140-158
Author(s):  
Isa Inuwa-Dutse
Keyword(s):  
Social Media ◽  
Public Discourse ◽  
Preventive Measures ◽  
State Of The Art ◽  
Fake News ◽  
Social Distancing ◽  
The Public ◽  
Toxic Impact ◽  
Online Social Media ◽  
Social Media Platforms

Conventional preventive measures during pandemics include social distancing and lockdown. Such measures in the time of social media brought about a new set of challenges – vulnerability to the toxic impact of online misinformation is high. A case in point is COVID-19. As the virus propagates, so does the associated misinformation and fake news about it leading to an infodemic. Since the outbreak, there has been a surge of studies investigating various aspects of the pandemic. Of interest to this chapter are studies centering on datasets from online social media platforms where the bulk of the public discourse happens. The main goal is to support the fight against negative infodemic by (1) contributing a diverse set of curated relevant datasets; (2) offering relevant areas to study using the datasets; and (3) demonstrating how relevant datasets, strategies, and state-of-the-art IT tools can be leveraged in managing the pandemic.

scholarly journals Online public discourse on artificial intelligence and ethics in China: context, content, and implications

AI & Society ◽  
2021 ◽  
Author(s):  
Yishu Mao ◽  
Kristin Shi-Kupfer
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
General Public ◽  
Public Discourse ◽  
It Industry ◽  
The Public ◽  
Ethical Implications ◽  
The World ◽  
Ai Ethics ◽  
Social Media Platforms

AbstractThe societal and ethical implications of artificial intelligence (AI) have sparked discussions among academics, policymakers and the public around the world. What has gone unnoticed so far are the likewise vibrant discussions in China. We analyzed a large sample of discussions about AI ethics on two Chinese social media platforms. Findings suggest that participants were diverse, and included scholars, IT industry actors, journalists, and members of the general public. They addressed a broad range of concerns associated with the application of AI in various fields. Some even gave recommendations on how to tackle these issues. We argue that these discussions are a valuable source for understanding the future trajectory of AI development in China as well as implications for global dialogue on AI governance.

scholarly journals Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data

10.2196/26780 ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. e26780
Author(s):  
Mohammad Al-Ramahi ◽  
Ahmed Elnoshokaty ◽  
Omar El-Gayar ◽  
Tareq Nasralah ◽  
Abdullah Wahbeh
Keyword(s):  
Social Media ◽  
Public Perception ◽  
Public Discourse ◽  
Population Control ◽  
Scientific Evidence ◽  
Pearson Correlation ◽  
The United States ◽  
Machine Learning Techniques ◽  
The Public ◽  
The Relationship

Background Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media. Objective This study aimed to investigate the topics associated with the public discourse against wearing masks in the United States. We also studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases. Methods We collected a total of 51,170 English tweets between January 1, 2020, and October 27, 2020, by searching for hashtags against wearing masks. We used machine learning techniques to analyze the data collected. We investigated the relationship between the volume of tweets against mask-wearing and the daily volume of new COVID-19 cases using a Pearson correlation analysis between the two-time series. Results The results and analysis showed that social media could help identify important insights related to wearing masks. The results of topic mining identified 10 categories or themes of user concerns dominated by (1) constitutional rights and freedom of choice; (2) conspiracy theory, population control, and big pharma; and (3) fake news, fake numbers, and fake pandemic. Altogether, these three categories represent almost 65% of the volume of tweets against wearing masks. The relationship between the volume of tweets against wearing masks and newly reported COVID-19 cases depicted a strong correlation wherein the rise in the volume of negative tweets led the rise in the number of new cases by 9 days. Conclusions These findings demonstrated the potential of mining social media for understanding the public discourse about public health issues such as wearing masks during the COVID-19 pandemic. The results emphasized the relationship between the discourse on social media and the potential impact on real events such as changing the course of the pandemic. Policy makers are advised to proactively address public perception and work on shaping this perception through raising awareness, debunking negative sentiments, and prioritizing early policy intervention toward the most prevalent topics.

scholarly journals Temporal and textual analysis of social media on collective discourses during the Zika virus pandemic

2019 ◽  
Author(s):  
May Oo Lwin ◽  
Jiahui Lu ◽  
Anita Sheldenkar ◽  
Ysa Marie Cayabyab ◽  
Zi Han Yee Andrew ◽  
...  
Keyword(s):  
Social Media ◽  
News Media ◽  
Public Discourse ◽  
Textual Analysis ◽  
Data Sources ◽  
Future Research ◽  
The Public ◽  
Social Media Platforms ◽  
Health Event ◽  
The Government

Abstract Background While existing studies have investigated the role of social media on health-related communication, little is known about the potential differences between different users groups on different social media platforms in responses to a health event. This study sets out to explore the online discourse of governmental authorities and the public in Singapore during the recent Zika pandemic in 2016. Methods Social media data were extracted from Facebook and Twitter using retroactive keyword sourcing of the word “Zika” to search for posts and a location filter of “Singapore”. Government posts, public posts, and replies to these original posts were included in the temporal and textual analysis. Results Overall, Facebook contained more government and individual content whereas Twitter had more content from news media accounts. Though the relative volume of Zika content from different data sources paralleled the peaks and troughs of Zika activities across time, discourses from different data sources differed in their temporal patterns, such that the public discourse died down faster than the government discourse after the outbreak was declared. In addition, the content of discourses differed among data sources. While government discourse included factual information of the disease, public discourse contained more elements of care such as worry about the risks to pregnant women, and elements of community such as well-wishes to each other. Conclusions Our study demonstrates the temporal and content differences between user groups and social media platforms in social media conversations during the Zika pandemic. It suggests that future research should examine the collective discourse of a health event by investigating social media discourses within varied sources rather than focusing on a singular social media platform and by one particular type of user.

scholarly journals Temporal and textual analysis of social media on collective discourses during the Zika virus pandemic

2020 ◽  
Author(s):  
May Oo Lwin ◽  
Jiahui Lu ◽  
Anita Sheldenkar ◽  
Ysa Marie Cayabyab ◽  
Andrew Yee Zi Han ◽  
...  
Keyword(s):  
Social Media ◽  
News Media ◽  
Public Discourse ◽  
Textual Analysis ◽  
Data Sources ◽  
Future Research ◽  
The Public ◽  
Social Media Platforms ◽  
Health Event ◽  
The Government

Abstract Background: While existing studies have investigated the role of social media on health-related communication, little is known about the potential differences between different users groups on different social media platforms in responses to a health event. This study sets out to explore the online discourse of governmental authorities and the public in Singapore during the recent Zika pandemic in 2016. Methods: Social media data were extracted from Facebook and Twitter using retroactive keyword sourcing of the word “Zika” to search for posts and a location filter of “Singapore”. Government posts, public posts, and replies to these original posts were included in the temporal and textual analysis. Results: Overall, Facebook contained more government and individual content whereas Twitter had more content from news media accounts. Though the relative volume of Zika content from different data sources paralleled the peaks and troughs of Zika activities across time, discourses from different data sources differed in their temporal patterns, such that the public discourse died down faster than the government discourse after the outbreak was declared. In addition, the content of discourses differed among data sources. While government discourse included factual information of the disease, public discourse contained more elements of care such as worry about the risks to pregnant women, and elements of community such as well-wishes to each other. Conclusions: Our study demonstrates the temporal and content differences between user groups and social media platforms in social media conversations during the Zika pandemic. It suggests that future research should examine the collective discourse of a health event by investigating social media discourses within varied sources rather than focusing on a singular social media platform and by one particular type of users.

scholarly journals Insults, criminalization, and calls for violence: Forms of hate speech and offensive language in German user comments on immigration

2021 ◽  
Author(s):  
Sünje Paasch-Colberg ◽  
Joachim Trebbe ◽  
Christian Strippel ◽  
Martin Emmer
Keyword(s):  
Social Media ◽  
Public Discourse ◽  
Hate Speech ◽  
Right Wing ◽  
The Public ◽  
Text Annotation ◽  
User Comments ◽  
News Websites ◽  
Social Media Platforms ◽  
Offensive Language

In the past decade, the public discourse on immigration in Germany has been strongly affected by right-wing populist, racist, and Islamophobic positions. This becomes evident especially in the comment sections of news websites and social media platforms, where user discussions often escalate and trigger hate comments against refugees and immigrants and also against journalists, politicians, and other groups. In view of the threatening consequences such sentiments can have for groups who are targeted by right-wing extremist violence, we take a closer look into such user discussions to gain detailed insights into the various forms of hate speech and offensive language against these groups. Using a modularized framework that goes beyond the common “hate/no-hate” dichotomy in the field, we conducted a structured text annotation of 5,031 user comments posted on German news websites and social media in March 2019. Most of the hate speech we found was directed against refugees and immigrants, while other groups were mostly exposed to various forms of offensive language. In comments containing hate speech, refugees and Muslims were frequently stereotyped as criminals, whereas extreme forms of hate speech, such as calls for violence, were rare in our data. These findings are discussed with a focus on their potential consequences for public discourse on immigration in Germany.

Exploring the Relationship Between Campaign Discourse on Facebook and the Public’s Comments: A Case Study of Incivility During the 2016 US Presidential Election

2020 ◽  
pp. 003232171989081
Author(s):  
Patrícia Rossini ◽  
Jennifer Stromer-Galley ◽  
Feifei Zhang
Keyword(s):  
Social Media ◽  
Public Discourse ◽  
Political Campaigns ◽  
Supervised Machine Learning ◽  
Presidential Debates ◽  
The Public ◽  
The Us ◽  
Negative Messages ◽  
The Relationship

Social media is now ubiquitously used by political campaigns, but less attention has been given to public discussions that take place on candidates’ free public accounts on social media. Also unclear is whether there is a relationship between campaign messaging and the tone of public comments. To address this gap, this article analyzes public comments on Facebook accounts of candidates Trump and Clinton during the US election presidential debates in 2016. We hypothesize that attack messages posted by the candidates predict uncivil reactions by the public and that the public is more likely to be uncivil when attacking candidates. We use content analysis, supervised machine learning, and text mining to analyze candidates’ posts and public comments. Our results suggest that Clinton was the target of substantially more uncivil comments. Negative messages by the candidates are not associated with incivility by the public, but comments are significantly more likely to be uncivil when the public is attacking candidates. These results suggest that the public discourse around political campaigns might be less affected by what campaigns post on social media than by the public’s own perceptions and feelings toward the candidates.

scholarly journals ‘Good food’ in an Instagram age: Rethinking hierarchies of culture, criticism and taste

2021 ◽  
pp. 136754942110557
Author(s):  
Zeena Feldman
Keyword(s):  
Social Media ◽  
Data Analysis ◽  
Empirical Data ◽  
Image Sharing ◽  
Social Media Platforms ◽  
Empirical Data Analysis ◽  
The Relationship ◽  
Knowledge Claims ◽  
Good Food ◽  
Insight Into

Through historical, economic and technological contextualisation and empirical data analysis, this article explores the cultural purchase the image-sharing app Instagram and the printed Michelin Guide have on contemporary food criticism. Both platforms contribute to popular understandings of ‘good food’. Yet, there are important functional and discursive distinctions in how culinary criticism is done in Instagram vis-à-vis Michelin. To that end, this article focuses on London’s restaurant scene and proposes the concept of the Instagram gaze as a means of understanding the representational repertoires and knowledge claims advanced by foodies on visual social media platforms. The Instagram gaze also facilitates insight into the relationship between Instagrammers’ culinary judgements and Michelin’ s.

scholarly journals Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data (Preprint)

2020 ◽  
Author(s):  
Mohammad Al-Ramahi ◽  
Ahmed Elnoshokaty ◽  
Omar El-Gayar ◽  
Tareq Nasralah ◽  
Abdullah Wahbeh
Keyword(s):  
Social Media ◽  
Public Perception ◽  
Public Discourse ◽  
Population Control ◽  
Scientific Evidence ◽  
Pearson Correlation ◽  
The United States ◽  
Machine Learning Techniques ◽  
The Public ◽  
The Relationship

BACKGROUND Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media. OBJECTIVE This study aimed to investigate the topics associated with the public discourse against wearing masks in the United States. We also studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases. METHODS We collected a total of 51,170 English tweets between January 1, 2020, and October 27, 2020, by searching for hashtags against wearing masks. We used machine learning techniques to analyze the data collected. We investigated the relationship between the volume of tweets against mask-wearing and the daily volume of new COVID-19 cases using a Pearson correlation analysis between the two-time series. RESULTS The results and analysis showed that social media could help identify important insights related to wearing masks. The results of topic mining identified 10 categories or themes of user concerns dominated by (1) constitutional rights and freedom of choice; (2) conspiracy theory, population control, and big pharma; and (3) fake news, fake numbers, and fake pandemic. Altogether, these three categories represent almost 65% of the volume of tweets against wearing masks. The relationship between the volume of tweets against wearing masks and newly reported COVID-19 cases depicted a strong correlation wherein the rise in the volume of negative tweets led the rise in the number of new cases by 9 days. CONCLUSIONS These findings demonstrated the potential of mining social media for understanding the public discourse about public health issues such as wearing masks during the COVID-19 pandemic. The results emphasized the relationship between the discourse on social media and the potential impact on real events such as changing the course of the pandemic. Policy makers are advised to proactively address public perception and work on shaping this perception through raising awareness, debunking negative sentiments, and prioritizing early policy intervention toward the most prevalent topics.

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