Examining multiplicity and dynamics of publics’ crisis narratives with large-scale Twitter data

Zhao, Xinyan; Zhan, Mengqi; Cheng, Jie

doi:10.1016/j.pubrev.2018.07.004

Cited by 48 publications

(20 citation statements)

References 58 publications

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“…In this study, we used Latent Dirichlet Allocation (LDA), one of the widely used topic models that groups words that frequently co-occur in documents into various topics. By providing the text input and setting the desired number of topics, LDA automatically produces a set of topics, words are allocated to the topics, and the topic proportions are attributed for each document [ 58 ]. We decided to use LDA, as findings yielded by prior studies indicate that it performs well with both long and short texts.…”

Section: Methodsmentioning

confidence: 99%

Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

Jiang¹,

Chu²,

Sun³

2021

JMIR Infodemiology

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Background During the early stages of the COVID-19 pandemic, developing safe and effective coronavirus vaccines was considered critical to arresting the spread of the disease. News and social media discussions have extensively covered the issue of coronavirus vaccines, with a mixture of vaccine advocacies, concerns, and oppositions. Objective This study aimed to uncover the emerging themes in Twitter users’ perceptions and attitudes toward vaccines during the early stages of the COVID-19 outbreak. Methods This study employed topic modeling to analyze tweets related to coronavirus vaccines at the start of the COVID-19 outbreak in the United States (February 21 to March 20, 2020). We created a predefined query (eg, “COVID” AND “vaccine”) to extract the tweet text and metadata (number of followers of the Twitter account and engagement metrics based on likes, comments, and retweeting) from the Meltwater database. After preprocessing the data, we tested Latent Dirichlet Allocation models to identify topics associated with these tweets. The model specifying 20 topics provided the best overall coherence, and each topic was interpreted based on its top associated terms. Results In total, we analyzed 100,209 tweets containing keywords related to coronavirus and vaccines. The 20 topics were further collapsed based on shared similarities, thereby generating 7 major themes. Our analysis characterized 26.3% (26,234/100,209) of the tweets as News Related to Coronavirus and Vaccine Development, 25.4% (25,425/100,209) as General Discussion and Seeking of Information on Coronavirus, 12.9% (12,882/100,209) as Financial Concerns, 12.7% (12,696/100,209) as Venting Negative Emotions, 9.9% (9908/100,209) as Prayers and Calls for Positivity, 8.1% (8155/100,209) as Efficacy of Vaccine and Treatment, and 4.9% (4909/100,209) as Conspiracies about Coronavirus and Its Vaccines. Different themes demonstrated some changes over time, mostly in close association with news or events related to vaccine developments. Twitter users who discussed conspiracy theories, the efficacy of vaccines and treatments, and financial concerns had more followers than those focused on other vaccine themes. The engagement level—the extent to which a tweet being retweeted, quoted, liked, or replied by other users—was similar among different themes, but tweets venting negative emotions yielded the lowest engagement. Conclusions This study enriches our understanding of public concerns over new vaccines or vaccine development at early stages of the outbreak, bearing implications for influencing vaccine attitudes and guiding public health efforts to cope with infectious disease outbreaks in the future. This study concluded that public concerns centered on general policy issues related to coronavirus vaccines and that the discussions were considerably mixed with political views when vaccines were not made available. Only a small proportion of tweets focused on conspiracy theories, but these tweets demonstrated high engagement levels and were often contributed by Twitter users with more influence.

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Section: Methodsmentioning

confidence: 99%

Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

Jiang¹,

Chu²,

Sun³

2021

JMIR Infodemiology

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“…The narrative paradigm in crisis communication is particularly relevant when considering crisis narratives created and shared on social media (Milan, 2015). For example, Zhao et al (2018) analyzed Twitter data to examine the dynamics of public crisis narratives around Chipotle’s E. coli contamination crisis, using the crisis and emergency risk communication (CERC) model (Seeger et al, 2005) as a framework to understand the process of crisis development. In the CERC model, crisis development follows a pattern that consists of the initial stage (when the crisis narratives are informational), the maintenance stage (when the crisis narratives contain both information and opinions), and the resolution stage (when the crisis narratives focus on “issues regarding cause, blame, responsibility, and adequacy of the response”) (Zhao et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Rethinking crisis dynamics from the perspective of online publics: A case study of Dolce & Gabbana’s China crisis

Ban

Lovari

2021

Public Relations Inquiry

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On November 18, 2018, the Italian fashion house Dolce & Gabbana (D&G) released a controversial video on all their social media channels. The video triggered an instant outcry from the general Chinese public, who called the video a racist caricature of Chinese culture. D&G responded to the crisis with several image repair strategies. This study examines D&G’s crisis communication efforts in the wake of this incident. Departing from corporate-oriented perspectives prevalent in the field of public relations, this study employs a dynamic, public-oriented view of crisis communication, which focuses on the dynamic, interactive process of crisis development from the standpoint of the publics. By analyzing communicative behavior on Twitter (an increasingly influential alternative public sphere in China) and in particular, comments and responses toward the crisis communication strategies employed by D&G, we have identified four prominent themes, or ways that publics framed their key messages against the corporation: “Apology not enough”; “Apology done badly”; “Call to unite against D&G”; and “Sarcasm, mockery, and abuse.” And they can be interpreted as a number of crisis communication strategies of the global, online publics. Based on our analysis of the D&G case, we discuss the theoretical implications of a dynamic, public-oriented perspective (DPOP) on crisis communication, highlighting its key areas of difference from the corporate-oriented perspective (COP).

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“…Those individuals who share valued opinions may become thought leaders in a crisis (Zhao, Zhan, & Wong, ). In addition, expressing opinions during disasters on social media helps publics cope with uncertainty and stress by creating and sharing their constructed realities (Zhao, Zhan, & Jie, ). This social construction of interpretations and understandings establishes intersubjective sensemaking (Suthers, ).…”

Section: Introductionmentioning

confidence: 99%

Understanding motivated publics during disasters: Examining message functions, frames, and styles of social media influentials and followers

Zhao

Zhan

Liu

2019

Contingencies & Crisis Mgmt

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There has been a growing body of research regarding how organizations and general publics communicate on social media during crises. Integrating the uses and gratifications perspective, the social‐mediated crisis communication model, and the framing approach, our study offers a consolidated framework explaining how and why motivated social media publics communicate during crises. Namely, we examined whether and how influentials and followers employed different message functions through communicative devices including frames and styles. A content analysis was conducted on 800 tweets sampled from influentials and followers discussing the 2017 Ariana Grande concert bombing disaster. Our results (N = 800) suggested that influentials and followers adopted distinct communicative functions on social media during the disaster. Influentials engaged in information sharing and support exchange, whereas followers engaged in opinion expression and emotional coping. Influentials and followers also adopted specific frames and styles to achieve these communicative functions. Our findings can help crisis communicators understand the needs, concerns, and communication features of different publics and construct effective messages to reach them.

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Examining multiplicity and dynamics of publics’ crisis narratives with large-scale Twitter data

Cited by 48 publications

References 58 publications

Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

Rethinking crisis dynamics from the perspective of online publics: A case study of Dolce & Gabbana’s China crisis

Understanding motivated publics during disasters: Examining message functions, frames, and styles of social media influentials and followers

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