“We Are Trying to Communicate the Best We Can”: Understanding Districts’ Communication on Twitter During the COVID-19 Pandemic

Michela, Esther; Rosenberg, Joshua M.; Kimmons, Royce; Sultana, Omiya; Burchfield, Macy A.; Thomas, Tayla

doi:10.1177/23328584221078542

Cited by 15 publications

(9 citation statements)

References 71 publications

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“…That is, while behavior management software focuses on both behavior and communication, other categories of software (most obviously including LMS and SISs , communication software and classroom management software ) are also associated with one of these two purposes. Indeed, in this context, even the identification of social media platforms in student responses has a certain logic to it; while we were personally surprised that students would see Twitter as equivalent to ClassDojo, it is nonetheless true that schools and school districts use this technology as a communication mechanism (Kimmons et al , 2018; Michela et al , 2022). For all the important differences between these categories of software – which we will address in the following section – there is a certain logic in many of these responses from a tool perspective.…”

Section: Discussionmentioning

confidence: 99%

Platforms, perceptions, and privacy: ethical implications of student conflation of educational technologies

Greenhalgh,

DiGiacomo,

Barriage

2023

ILS

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Purpose The purpose of this paper is to examine how higher education students think about educational technologies they have previously used – and the implications of this understanding for their awareness of datafication and privacy issues in a postsecondary context. Design/methodology/approach The authors conducted two surveys about students’ experience with the ClassDojo platform during their secondary education. In both surveys, the authors included a question asking students to identify which ClassDojo-like platform they used in school. For this study, the authors examined responses to these screening questions, identifying the technologies that responses referred to and sorting technologies into categories. Findings Students identified a wide range of technologies when prompted to identify a technology similar to ClassDojo. Many responses suggested students have a broad, monolithic understanding of educational technology. This suggests the prevalence of a utilitarian tool perspective (rather than a platform perspective) that may be entrenched by the time that students reach higher education, hampering efforts to inform and educate them in that context. Originality/value To the best of the authors’ knowledge, there are few studies of students’ conflation of educational technologies in the extant literature. Furthermore, the platform perspective emphasized in this manuscript remains relatively rare in many fields associated with educational technology.

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Section: Discussionmentioning

confidence: 99%

Platforms, perceptions, and privacy: ethical implications of student conflation of educational technologies

Greenhalgh,

DiGiacomo,

Barriage

2023

ILS

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“…It is worth noting that, in comparison to other qualitative inquiries on Twitter data, the sample size in this study is not an outlier. For instance, Michaela et al 66 analyzed 1357 tweets posted over approximately one month to investigate district communication during the pandemic. Nisch 67 examined public opinion on Finland joining NATO by using a subset of 500 random tweets, which were manually reviewed and analyzed.…”

Section: Discussionmentioning

confidence: 99%

Digital inclusion: A mixed-method study of user behavior and content on Twitter

Salzmann-Erikson

2023

DIGITAL HEALTH

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Objective This study is the first to explore user behavior and characterize the content shared about digital inclusion on Twitter. Methods This mixed-methods research consists of 14,000 tweets featuring the hashtag “#digitalinclusion,” posted on Twitter over 15 months. A machine learning technique, latent Dirichlet allocation, was utilized to discover abstract topics within the tweets statistically. The algorithm identified important keywords and text associated with each topic by modeling the underlying word co-occurrence patterns in the dataset. A manual qualitative content analysis was applied to the qualitative data (1000 tweets). Results Tweets containing #digitalinclusion are driven by four motives: 1) warning against the risks of digital exclusion; 2) tweets that promote actions to increase digital inclusion; 3) tweets that call for others to take action to improve digitalization; and 4) tweets that are neutral but fuel the debate by being active. Quantitative analysis revealed that users discussing digital inclusion come from various continents, including the USA, Europe, Africa, and Asia. There were 3931 unique user accounts, with individuals posting between one and 368 tweets. Approximately half of the tweets contained some embedded media. Conclusion The study concludes that digital inclusion is a subject that engages Twitter users worldwide. Tweets that were associated with community and local initiatives and sustainable development had the highest engagement in terms of the number of retweets and likes. The interpretation is that digital inclusion is crucial for achieving equity in living conditions and enhancing access to health information and services. While initiatives to increase digital inclusion are underway, Twitter users call for more efforts to prevent growing digital exclusion. Twitter, as a social media platform, is valuable for studying the motivations that drive digital inclusion and help counter digital exclusion.

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“…Data mining assist researchers to understand news with new ways [14]. With 695,051 collected BBC news on counterterrorism, we conducted a text analysis with LDA topic modeling, and generated 20 topics with 5 themes.…”

Section: Discussionmentioning

confidence: 99%

Getting insights from news data mining: a case of BBC's counter-terrorism news text analysis

Li¹,

Jia²,

Liu³

et al. 2022

Second International Symposium on Computer Technology and Information Science (ISCTIS 2022)

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Data mining plays an important role in getting insights from news text. This study collected 695,051 English-language news reports on terrorism and counter-terrorism from March 2017 to March 2018 in BBC news, and conducted a text analysis with LDA topic modeling. 20 topics and 5 themes were classified and it was disclosed that major themes include that: (1) BBC focused on constructing local discourse structure, (2) Comparing the news reports at home and abroad, and (3) Historical origins, the development in ancient and modern times and a trial of strength between different countries.

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“We Are Trying to Communicate the Best We Can”: Understanding Districts’ Communication on Twitter During the COVID-19 Pandemic

Cited by 15 publications

References 71 publications

Platforms, perceptions, and privacy: ethical implications of student conflation of educational technologies

Platforms, perceptions, and privacy: ethical implications of student conflation of educational technologies

Digital inclusion: A mixed-method study of user behavior and content on Twitter

Getting insights from news data mining: a case of BBC's counter-terrorism news text analysis

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