Predicting the Spread of a New Tweet in Twitter

Anwar, Musfique; Li, Jianxin; Liu, Chengfei

doi:10.1007/978-3-319-19548-3_9

Cited by 3 publications

(7 citation statements)

References 12 publications

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“…By identifying MSIs who are influential on SNSs, health information providers can realize their purposes of disseminating health awareness messages on a large scale at a low marketing cost to the community [16] to promote the adoption of healthy lifestyles. Since social media facilitate the dissemination of information to other users or the public more widely and rapidly [69,70], while our study has shown that health-related information and the communicative strategy of connectivity foster the sharing of MSI posts, MSIs can mobilize these strategies to reach a larger audience and deliver health care. Because MSIs are a reliable source of health-related information, the public could be persuaded to change their health behavior.…”

Section: Theoretical and Practical Implicationsmentioning

confidence: 83%

“…Our results offered consistent evidence that health-related content as opposed to the other dimensions contributes to the highest level of public engagement in terms of the number of likes, comments, and especially shares. Sharing, which is a distinct characteristic of social media, enables users or the public to reproduce the information by sharing it [ 69 ] with a large number of users. Thus, sharing as a form of engagement, which enables users to link the MSI post to their social group [ 70 ], is vital in disseminating health-related information more widely and rapidly.…”

Section: Discussionmentioning

confidence: 99%

“…enables users or the public to reproduce the information by sharing it [69] with a large number of users. Thus, sharing as a form of engagement, which enables users to link the MSI post to their social group [70], is vital in disseminating health-related information more widely and rapidly.…”

Section: Plos Onementioning

confidence: 99%

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Exploring drivers for public engagement in social media communication with medical social influencers in China

Ngai

Singh

2020

PLoS ONE

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Social networking sites offer an important means for increasing the accessibility and enabling new forms of health communication between the public and medical social influencers (MSIs). MSIs have a social presence and are perceived as a credible source of healthrelated information. A research gap, however, exists in understanding the communication strategies employed by MSIs and the factors driving the public to engage in health communication with MSIs. This study, therefore, developed a new conceptual framework incorporating health communication, dialogic and interpersonal communication by employing quantitative content analysis to examine public engagement with MSI communication on the largest microblogging site in China, Sina Weibo. The analysis yielded insights into how the usefulness of health-related information provided alongside the interactive dialogue and affective practices played an active role in engaging the public. The public sought healthrelated information primarily to address issues of concern for well-being and a high level of engagement in terms of online shares, likes, and comments was found. The use of multimedia made the site more appealing, resulting in likes while the expression of emotions by MSIs generated likes and comments. The need to connect with other online users and have a sense of community was reflected in engagement through sharing useful MSI posts by the public. By identifying influential MSIs on social networking sites, health information providers such as organizations and the government can raise awareness of health issues to foster a healthy lifestyle and contribute to better living in the community.

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Section: Theoretical and Practical Implicationsmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 99%

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Exploring drivers for public engagement in social media communication with medical social influencers in China

Ngai

Singh

2020

PLoS ONE

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“…Previous researchers who have studied all functions of social media communications have argued that one of the important proxies to measure social media communications' ultimate effectiveness is its reproduction rate: for example, in the case of communications via Twitter, retweets (Anwar et al , 2015; Chung, 2017; Hoang and Lim, 2012; Lim and Lee-Won, 2017). A distinctive characteristic of social media compared to other marketing channels is that any user can reproduce the information to an unlimited extent by sharing and re-posting (Anwar et al , 2015). Social media are connected networks among a massive number of users, and when users reproduce information in these clustered connections, it helps disseminate information more rapidly and widely (Chung, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The reason why previous researchers have emphasized the importance of information diffusion via retweets is because such information reproduction maximizes the original post's visibility and reach and thus makes it more effective (Anwar et al , 2015). Therefore, the reproduction rate, such as that in retweets, measures the original account owner's social media communications' effectiveness (Anwar et al , 2015), which also often is referred to as the word-of-mouth effect (Hoang and Lim, 2012). Noting retweets' importance, previous researchers have investigated the process of information diffusion via retweets actively.…”

Section: Literature Reviewmentioning

confidence: 99%

Understanding the information diffusion of tweets of a non-profit organization that targets female audiences: an examination of Women Who Code's tweets

Chung

Woo

Lee

2020

JCOM

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PurposeThere is a growing interest in the way non-profit organizations can use Twitter strategically to communicate their message, but little attention has been paid to the way content categories and features may facilitate retweets of messages of a non-profit organization that targets women as its audience. Based on stakeholder theory, this study aims to fill this gap by analyzing Women Who Code (WWC)'s tweets to examine whether there are any differences in the number of retweets with respect to the content categories (information, community or action) and features (hashtags, emojis, photos, videos and URLs) in its Twitter communications.Design/methodology/approachWWC's original tweets that were posted during a one-year period from February 20, 2018 to February 20, 2019 were collected using a Twitter analytics tool. The content categories for each tweet were coded, and the number of hashtags and emojis used and the inclusion of photos, videos and URLs were noted. A negative binomial regression model was used to address the research questions.FindingsThe findings showed that with respect to the content categories, community and action-based tweets were retweeted less frequently than informational tweets. With respect to the content features, the results showed that using emojis or URLs in a tweet affected retweets positively, while including hashtags or a video affected them negatively. Further, using photos or images in a tweet had no significant effect on retweets.Originality/valueThese findings contribute to our understanding of non-profit organizations' use of Twitter and provide practical implications for the way non-profit organizations that target female audiences interested in technology can disseminate their messages more strategically.

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Epidemic model based visibility estimation in Online Social Networks

Rathore

Tripathy

2018

2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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Predicting the Spread of a New Tweet in Twitter

Cited by 3 publications

References 12 publications

Exploring drivers for public engagement in social media communication with medical social influencers in China

Exploring drivers for public engagement in social media communication with medical social influencers in China

Understanding the information diffusion of tweets of a non-profit organization that targets female audiences: an examination of Women Who Code's tweets

Epidemic model based visibility estimation in Online Social Networks

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