The Why We Retweet scale

Majmundar, Anuja; Allem, Jon-Patrick; Cruz, Tess Boley; Unger, Jennifer B.

doi:10.1371/journal.pone.0206076

Cited by 42 publications

(27 citation statements)

References 26 publications

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“…A common refrain on Twitter is that "likes and/or retweets do not equal endorsements," and the same can be said here. Though we find that simpler language corresponds with more social engagements, we cannot say whether these behaviors indicate more liking or support for the content in question given that people commonly engage with content they dislike or disagree with as well (40,41). Although we acknowledge our inability to address the motivation for engagement directly, the size and diversity of our samples suggests the presence of differential motivations for engagement are likely distributed evenly across the same sample.…”

Section: Discussionmentioning

confidence: 70%

The predictive utility of word familiarity for online engagements and funding

Markowitz

Shulman

2021

Proc. Natl. Acad. Sci. U.S.A.

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Metacognitive frameworks such as processing fluency often suggest people respond more favorably to simple and common language versus complex and technical language. It is easier for people to process information that is simple and nontechnical compared to complex information, therefore leading to more engagement with targets. In two studies covering 12 field samples (total n = 1,064,533), we establish and replicate this simpler-is-better phenomenon by demonstrating people engage more with nontechnical language when giving their time and attention (e.g., simple online language tends to receive more social engagements). However, people respond to complex language when giving their money (e.g., complex language within charitable giving campaigns and grant abstracts tend to receive more money). This evidence suggests people engage with the heuristic of complex language differently depending on a time or money target. These results underscore language as a lens into social and psychological processes and computational methods to measure text patterns at scale.

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Section: Discussionmentioning

confidence: 70%

The predictive utility of word familiarity for online engagements and funding

Markowitz

Shulman

2021

Proc. Natl. Acad. Sci. U.S.A.

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“…Prior work has shown that a retweet demonstrates support for the author of the original tweet, but the significance of a retweeted message remains unclear. 23 Future studies are needed to examine how support interventions that use social media can be designed effectively.…”

Section: Discussionmentioning

confidence: 99%

Examining Public Communication About Kidney Cancer on Twitter

Sedrak

Salgia

Bergerot

et al. 2019

JCO Clinical Cancer Informatics

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PURPOSE Several studies have described the content of Twitter conversations about lung, breast, and prostate cancer, but little is known about how the public uses Twitter to discuss kidney cancer. We sought to characterize the content of conversations on Twitter about kidney cancer and the participants engaged in these dialogues. METHODS This qualitative study analyzed the content of 2,097 tweets that contained the key words kidney cancer from August 1 to 22, 2017. Tweets were categorized by content domain of conversations related to kidney cancer on Twitter and user types of participants in these dialogues. RESULTS Among the 2,097 kidney cancer–related tweets analyzed, 858 (41.4%) were authored by individuals, 865 (41.2%) by organizations, and 364 (17.4%) by media sites. The most common content discussed was support (29.3%) and treatment (26.5%). Among the 2,097 tweets, 825 were unique tweets, and 1,272 were retweets. The most common unique tweets were about clinical trials (23.9%), most often authored by media sites. The most common retweets were about treatment (38.5%), most often authored by organizations. CONCLUSION Twitter dialogues about kidney cancer are most commonly related to support and treatment. Our findings provide insights that may inform the design of new interventions that use social media as a tool to improve communication of kidney cancer information. Additional efforts are needed to improve our understanding of the value and direct utility of social media in improving kidney cancer care.

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“…Due to this asymmetry, users can re-create and reinforce traditional hierarchical network structures in Twitter by relying on just a few information sources or by choosing to limit interactions to a select group of similar others (Himelboim et al, 2017). Thus, the connections built among users are indicators of information sharing and network structures reflect patterns of information flow (Himelboim et al, 2017;Majmundar et al, 2018).…”

mentioning

confidence: 99%

COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers

Kim

Valente

2020

Connections

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Coronavirus disease of 2019 (COVID-19)'s devastating effects on the physical and mental health of the public are unlike previous medical crises, in part because of people's collective access to communication technologies. Unfortunately, a clear understanding of the diffusion of health information on social media is lacking, which has a potentially negative impact on the effectiveness of emergency communication. This study applied social network analysis approaches to examine patterns of #COVID19 information flow on Twitter. A total of 1,404,496 publicly available tweets from 946,940 U.S. users were retrieved and analyzed. Particular attention was paid to the structures of retweet and mention networks and identification of influential users: information sources, disseminators, and brokers. Overall, COVID-19 information was not transmitted efficiently. Findings pointed to the importance of fostering connections between clusters to promote the diffusion in both networks. Lots of localized clusters limited the spread of timely information, causing difficulty in establishing any momentum in shaping urgent public actions. Rather than health and communication professionals, there was dominant involvement of non-professional users responsible for major COVID-19 information generation and dissemination, suggesting a lack of credibility and accuracy in the information. Inadequate influence of health officials and government agencies in brokering information contributed to concerns about the spread of dis/misinformation to the public. Significant differences in the type of influential users existed across roles and across networks. Conceptual and practical implications for emergency communication strategies are discussed.

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The Why We Retweet scale

Cited by 42 publications

References 26 publications

The predictive utility of word familiarity for online engagements and funding

The predictive utility of word familiarity for online engagements and funding

Examining Public Communication About Kidney Cancer on Twitter

COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers

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