Strange Frame Fellows: The Evolution of Discursive Framing in the Opt-Out Testing Movement

2021 ◽  
Vol 123 (5) ◽  
pp. 1-32 ◽  
Author(s):  
Richard Paquin Morel

Background/context In recent years, opposition to accountability policies and associated testing has manifested in widespread boycotts of annual tests—mobilized as the “opt-out movement.” A central challenge facing any movement is the need to recruit and mobilize participants. Key to this process is framing—a discursive tactic in which activists present social issues as problems that require collective action to solve. Such framing often relies on compatible political and ideological commitments among activists and potential recruits. Yet the opt-out movement has successfully mobilized widespread boycotts in diverse communities. How have participants in the movement framed issues relating to testing and accountability? Purpose/objective/research question/focus of study I explore the discursive tactics of participants in the opt-out movement by analyzing how they frame issues related to testing and accountability over time. I ask two research questions: (1) What frames did participants in opt-out-aligned social media groups use to convince others that standardized accountability tests are a problem and build support for the movement? (2) To what extent and how did the deployment of frames change over time? Research design I conducted a mixed-methods study combining qualitative content analysis to identify frames and computational analysis to describe their co-deployment over time. Data collection and analysis I compiled a text corpus of posts to opt-out-aligned social media pages from 2010–2014. I analyzed posts using open coding to identify frames used by participants in online communities. Frames were categorized by their orientation—the general way in which they framed the problem of testing and accountability. I then analyzed the co-deployment of frames using network analysis and hierarchical clustering. Conclusions/recommendations The longitudinal analysis of frames reveals key differences in the frames used by participants. While more politically oriented frames—those characterizing testing as a social issue affecting the public schools at large—were common in early stages of the movement, less overtly political frames—those characterizing testing as an individual issue affecting children and local schools or a technical issue—became more prominent over time. Over time, socially oriented frames became decoupled from other frames, showing independent patterns of deployment. This suggests that the movement may have benefited from de-emphasizing politically oriented frames, but that it lacked an overarching shared narrative, which has the potential to limit how it might affect accountability policies and testing.

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Milad Mirbabaie ◽  
Stefan Stieglitz ◽  
Felix Brünker

PurposeThe purpose of this study is to investigate communication on Twitter during two unpredicted crises (the Manchester bombings and the Munich shooting) and one natural disaster (Hurricane Harvey). The study contributes to understanding the dynamics of convergence behaviour archetypes during crises.Design/methodology/approachThe authors collected Twitter data and analysed approximately 7.5 million relevant cases. The communication was examined using social network analysis techniques and manual content analysis to identify convergence behaviour archetypes (CBAs). The dynamics and development of CBAs over time in crisis communication were also investigated.FindingsThe results revealed the dynamics of influential CBAs emerging in specific stages of a crisis situation. The authors derived a conceptual visualisation of convergence behaviour in social media crisis communication and introduced the terms hidden and visible network-layer to further understanding of the complexity of crisis communication.Research limitations/implicationsThe results emphasise the importance of well-prepared emergency management agencies and support the following recommendations: (1) continuous and (2) transparent communication during the crisis event as well as (3) informing the public about central information distributors from the start of the crisis are vital.Originality/valueThe study uncovered the dynamics of crisis-affected behaviour on social media during three cases. It provides a novel perspective that broadens our understanding of complex crisis communication on social media and contributes to existing knowledge of the complexity of crisis communication as well as convergence behaviour.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aasif Ahmad Mir ◽  
Sevukan Rathinam ◽  
Sumeer Gul

PurposeTwitter is gaining popularity as a microblogging and social networking service to discuss various social issues. Coronavirus disease 2019 (COVID-19) has become a global pandemic and is discussed worldwide. Social media is an instant platform to deliberate various dimensions of COVID-19. The purpose of the study is to explore and analyze the public sentiments related to COVID-19 vaccines across the Twitter messages (positive, neutral, and negative) and the impact tweets make across digital social circles.Design/methodology/approachTo fetch the vaccine-related posts, a manual examination of randomly selected 500 tweets was carried out to identify the popular hashtags relevant to the vaccine conversation. It was found that the hashtags “covid19vaccine” and “coronavirusvaccine” were the two popular hashtags used to discuss the communications related to COVID-19 vaccines. 23,575 global tweets available in public domain were retrieved through “Twitter Application Programming Interface” (API), using “Orange Software”, an open-source machine learning, data visualization and data mining toolkit. The study was confined to the tweets posted in English language only. The default data cleaning and preprocessing techniques available in the “Orange Software” were applied to the dataset, which include “transformation”, “tokenization” and “filtering”. The “Valence Aware Dictionary for sEntiment Reasoning” (VADER) tool was used for classification of tweets to determine the tweet sentiments (positive, neutral and negative) as well as the degree of sentiments (compound score also known as sentiment score). To assess the influence/impact of tweets account wise (verified and unverified) and sentiment wise (positive, neutral, and negative), the retweets and likes, which offer a sort of reward or acknowledgment of tweets, were used.FindingsA gradual decline in the number of tweets over the time is observed. Majority (11,205; 47.52%) of tweets express positive sentiments, followed by neutral (7,948; 33.71%) and negative sentiments (4,422; 18.75%), respectively. The study also signifies a substantial difference between the impact of tweets tweeted by verified and unverified users. The tweets related to verified users have a higher impact both in terms of retweets (65.91%) and likes (84.62%) compared to the tweets tweeted by unverified users. Tweets expressing positive sentiments have the highest impact both in terms of likes (mean = 10.48) and retweets (mean = 3.07) compared to those that express neutral or negative sentiments.Research limitations/implicationsThe main limitation of the study is that the sentiments of the people expressed over one single social platform, that is, Twitter have been studied which cannot generalize the global public perceptions. There can be a variation in the results when the datasets from other social media platforms will be studied.Practical implicationsThe study will help to know the people's sentiments and beliefs toward the COVID-19 vaccines. Sentiments that people hold about the COVID-19 vaccines are studied, which will help health policymakers understand the polarity (positive, negative, and neutral) of the tweets and thus see the public reaction and reflect the types of information people are exposed to about vaccines. The study can aid the health sectors to intensify positive messages and eliminate negative messages for an enhanced vaccination uptake. The research can also help design more operative vaccine-advocating communication by customizing messages using the obtained knowledge from the sentiments and opinions about the vaccines.Originality/valueThe paper focuses on an essential aspect of COVID-19 vaccines and how people express themselves (positively, neutrally and negatively) on Twitter.


2018 ◽  
Vol 19 (2) ◽  
pp. 178-191 ◽  
Author(s):  
Victoria F Burns ◽  
Anne Blumenthal ◽  
Kathleen C Sitter

Social media technologies continue to change the academic landscape. Twitter has become particularly popular in research arenas including social work and is being used for fieldwork, knowledge mobilization activities, advocacy, and professional networking. Although there has been some consideration of the benefits and risks of using social media in academia, little has been written from a qualitative social work perspective. Drawing on the example of Twitter, this article redresses this gap in the literature, by exploring how social media is changing the way research is conducted and promoted in relation to (1) measuring scholarly impact via altmetrics; (2) engaging with research participants; (3) networking and making collegial connections; and (4) advocating for social issues in the public realm. As we highlight tensions in each of these four areas, a key concern is how and for whom social media is contributing to the changing meaning of scholarly impact and engagement in research communities. We draw specific attention to how the inequalities that exist in academia writ large may be amplified on social media thus affecting overall engagement and perceived impact for researchers from marginalized social locations (e.g. gender, race, sexual orientation). We conclude by discussing specific implications of using social media in qualitative social work research and provide suggestions for future areas of inquiry.


2020 ◽  
Vol 6 (2) ◽  
pp. 205630512091992
Author(s):  
Zaida Orth ◽  
Michelle Andipatin ◽  
Ferdinand C Mukumbang ◽  
Brian van Wyk

Social media is becoming a valuable resource for hosting activism as illustrated in the rise of the hashtag movements, such as #MeToo and #Endrapeculture, used to speak out against rape culture. In this article, we discuss the use of social media as the source and object of research, using the case of the 2016 South African #nakedprotest. We used naturalistic observation on Facebook comment threads and followed these up with online Facebook focus groups. Qualitative content analysis and thematic decomposition analysis were used, respectively, to explore online discourses of rape culture. We found that the use of social media as a medium for data collection is valuable for exploring trending social issues such as the rape culture #nakedprotest. We uncovered that social media offers researchers the opportunity to collect, analyze, and triangulate rich qualitative data for the exploration of social phenomena. This study illustrates the usefulness of social media as a pedagogical instrument.


2021 ◽  
Author(s):  
Siru Liu ◽  
Jili Li ◽  
Jialin Liu

BACKGROUND The COVID-19 vaccine is considered to be the most promising approach to alleviate the pandemic. However, in recent surveys, acceptance of the COVID-19 vaccine has been low. To design more effective outreach interventions, there is an urgent need to understand public perceptions of COVID-19 vaccines. OBJECTIVE Our objective was to analyze the potential of leveraging transfer learning to detect tweets containing opinions, attitudes, and behavioral intentions toward COVID-19 vaccines, and to explore temporal trends as well as automatically extract topics across a large number of tweets. METHODS We developed machine learning and transfer learning models to classify tweets, followed by temporal analysis and topic modeling on a dataset of COVID-19 vaccine–related tweets posted from November 1, 2020 to January 31, 2021. We used the F1 values as the primary outcome to compare the performance of machine learning and transfer learning models. The statistical values and <i>P</i> values from the Augmented Dickey-Fuller test were used to assess whether users’ perceptions changed over time. The main topics in tweets were extracted by latent Dirichlet allocation analysis. RESULTS We collected 2,678,372 tweets related to COVID-19 vaccines from 841,978 unique users and annotated 5000 tweets. The F1 values of transfer learning models were 0.792 (95% CI 0.789-0.795), 0.578 (95% CI 0.572-0.584), and 0.614 (95% CI 0.606-0.622) for these three tasks, which significantly outperformed the machine learning models (logistic regression, random forest, and support vector machine). The prevalence of tweets containing attitudes and behavioral intentions varied significantly over time. Specifically, tweets containing positive behavioral intentions increased significantly in December 2020. In addition, we selected tweets in the following categories: positive attitudes, negative attitudes, positive behavioral intentions, and negative behavioral intentions. We then identified 10 main topics and relevant terms for each category. CONCLUSIONS Overall, we provided a method to automatically analyze the public understanding of COVID-19 vaccines from real-time data in social media, which can be used to tailor educational programs and other interventions to effectively promote the public acceptance of COVID-19 vaccines.


2021 ◽  
Author(s):  
◽  
Gunilla Elleholm Jensen

<p>Knowledge and information give people the power to make decisions and to act; they are the key to the success of real-time decision making. Social media can be valuable in emergencies where information can be shared to save lives and minimise the human and social impact. Fostering information quality is important in order to validate the information collected for decision making. With the empowerment of the general public and the abundance of information on social media, information quality becomes central to achieving an effective and efficient outcome in emergency response and saving lives. A gap exists in the research in the area of information quality in the use of online social media for emergency management in New Zealand. The research question for this study is: What are the key criteria for fostering information quality in the use of online social media for emergency management in New Zealand? How are they achieved? The data collection method employed was in-depth interviews of members of emergency management organisations in New Zealand. The interviews were followed by participant check. Previous research has identified accuracy, consistency and relevancy as the most frequently acknowledged criteria for information quality. This study found that the three key criteria for information quality in the use of online social media for emergency management in New Zealand are: Using verified and validated information; Using timely information; Building and using networks. There were two conflicts between the criteria: The need to dispel rumours or get time critical information out to the public can be in conflict with making sure that information is verified and trustworthy. The other conflict lies in the desire to control communication on social media, which hinders sharing of information and engagement with the public. It was found that the key criteria for information quality can be achieved by engaging with followers, so that their shared information can be included in the EOCs standard verification processes, and at the same time letting the followers know what the time frame is for new information releases.</p>


2018 ◽  
Vol 17 (3) ◽  
pp. 675-701 ◽  
Author(s):  
Kendra Bischoff ◽  
Laura Tach

In an education system that draws students from residentially based attendance zones, schools are local institutions that reflect the racial composition of their surrounding communities. However, with opportunities to opt out of the zoned public school system, the social and economic contexts of neighborhoods may affect the demographic link between neighborhoods and their public neighborhood schools. Using spatial data on school attendance zones, we estimate the associations between the racial composition of elementary schools and their local neighborhoods, and we investigate how neighborhood factors shape the loose or tight demographic coupling of these parallel social contexts. The results show that greater social distance among residents within neighborhoods, as well as the availability of educational exit options, results in neighborhood public schools that are less reflective of their surrounding communities. In addition, we show that suburban schools are more demographically similar to their neighborhood attendance zones than are urban schools.


Psych ◽  
2022 ◽  
Vol 4 (1) ◽  
pp. 60-70
Author(s):  
Melissa MacKay ◽  
Taylor Colangeli ◽  
Sydney Gosselin ◽  
Sophie Neumann ◽  
Andrew Papadopoulos

During the COVID-19 pandemic, key stakeholders have used social media to rapidly disseminate essential information to the public to help them make informed health-related decisions. Our research examined how the public responded to official actors’ Facebook posts during COVID-19 and examined the comment sentiment and post engagement rates. CBC News and CTV News received a greater proportion of negative comments and a lower average post engagement rate compared with Healthy Canadians. Additionally, the proportion of negative and positive comments varied over time for all sources; however, over 30% of the comments for all three actors were consistently negative. Key stakeholders should monitor the public’s response to their social media posts and adapt their messages to increase the effectiveness of their crisis communication efforts to encourage the adoption of protective measures.


Author(s):  
Yang Yang ◽  
Yingying Su

With the development of the Internet, social networking sites have empowered the public to directly express their views about social issues and hence contribute to social change. As a new type of voice behavior, public voice on social media has aroused wide concern among scholars. However, why public voice is expressed and how it influences social development and betterment in times of public health emergencies remains unstudied. A key point is whether governments can take effective countermeasures when faced with public health emergencies. In such situation, public voice is of great significance in the formulation and implementation of coping policies. This qualitive study uses China’s Health Code policy under COVID-19 to explore why the public performs voice behavior on social media and how this influences policy evolution and product innovation through cooperative governance. A stimulus-cognition-emotion-behavior model is established to explain public voice, indicating that it is influenced by cognitive processes and public emotions under policy stimulus. What is more, as a form of public participation in cooperative governance, public voice plays a significant role in promoting policy evolution and product innovation, and represents a useful form of cooperation with governments and enterprises to jointly maintain social stability under public health emergencies


2020 ◽  
Author(s):  
Kimia Pourmohammadi ◽  
Seyyed Hakimzadeh ◽  
Pivand Bastani

BACKGROUND Under these circumstances, social media is constantly covering the news and the related information via films, voices, clips, and texts; however, these reports are sometimes challenging outbreak response efforts. For instance, the misinformation and conspiracy theories spread via social media have generated panic and mistrust among the general public, diverted attention away from the outbreak response, and impeded the activities of health-care workers (6). Another evidence shows that many public safety agencies and organizations face the challenge of reducing the spread of false information distributed via social media (9). Accordingly, the aim of this study was to analyze the contents of information shared via virtual social media over the three weeks since the formal confirmation of COVID-19 outbreak in the Islamic Republic of Iran. OBJECTIVE According to the effective role of social media in communicating risk information to the public, the aim of this study was to analyze the contents of information shared via virtual social media over the three weeks since the formal confirmation of COVID-19 outbreak in the Islamic Republic of Iran. METHODS This qualitative discourse analysis was conducted on the contents of three more common virtual social networks (Instagram, WhatsApp, and Telegram) from Feb20 to March 11, 2020 in Iran. Four steps of defining the research question and selecting the content of analysis, gathering information and theory on the context, analyzing the content for themes and patterns and reviewing the results and drawing conclusions were conducted. RESULTS Based on the results, the contents of social media in the analysis duration were allocated four main categories related to the COVID-19 outbreak including political, social, health, and economic issues CONCLUSIONS It seems that all three social Medias have an effective role to share public information, especially those that are related to the public health and health education but at the same time, the analyzed social media have created the sense of panic and fear, particularly in the scopes of social, economic, and political issues.


Sign in / Sign up

Export Citation Format

Share Document