Statistically Modeling the Effectiveness of Disaster Information in Social Media

Zhu, Jiasong; Xiong, Fei; Piao, Dongzhen; Liu, Yun; Zhang, Ying

doi:10.1109/ghtc.2011.48

Cited by 33 publications

(24 citation statements)

References 4 publications

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“…This development has enabled researchers to examine the message content features associated with higher rates of message retransmission (30,31). Researchers note the emergence of user conventions when retweeting, such as the inclusion of a RT (indicating a retransmitted message or retweet), # (hashtag), and web link or URL (32).…”

Section: Message Contentmentioning

confidence: 99%

“…Although previous studies of public message retransmission have examined message content by focusing on trending topics (31), performing sentiment analysis (30), or analyzing word choice through its frequency of use (25,26), these approaches do not include message style features-that is, how the message is written to improve message clarity. Rhetorical strategies-such as the use of punctuation, the choice of sentence style, or the capitalization of words or phrases-are additional message features that may affect perceptions of message salience among recipients and subsequently influence their likelihood to retransmit a message.…”

Section: Message Stylementioning

confidence: 99%

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A cross-hazard analysis of terse message retransmission on Twitter

Sutton

Gibson

Phillips

et al. 2015

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

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For decades, public warning messages have been relayed via broadcast information channels, including radio and television; more recently, risk communication channels have expanded to include social media sites, where messages can be easily amplified by user retransmission. This research examines the factors that predict the extent of retransmission for official hazard communications disseminated via Twitter. Using data from events involving five different hazards, we identity three types of attributes-local network properties, message content, and message style-that jointly amplify and/or attenuate the retransmission of official communications under imminent threat. We find that the use of an agreed-upon hashtag and the number of users following an official account positively influence message retransmission, as does message content describing hazard impacts or emphasizing cohesion among users. By contrast, messages directed at individuals, expressing gratitude, or including a URL were less widely disseminated than similar messages without these features. Our findings suggest that some measures commonly taken to convey additional information to the public (e.g., URL inclusion) may come at a cost in terms of message amplification; on the other hand, some types of content not traditionally emphasized in guidance on hazard communication may enhance retransmission rates.nder conditions of imminent threat, rapid communication of warning information to the public is a primary strategy for decreasing loss of life and increasing public safety by eliciting protective actions from those at risk (1). For decades, public warnings have been relayed via mass media channels, including radio, broadcast television, and sirens (2). With the advent of social computing, warnings have begun to be disseminated via online social networks (OSNs), where messages can be more easily propagated and amplified by the user population (3-6). Risk amplification via message retransmission in this setting is important because it enables a message to reach individuals beyond the sender's direct contacts, increasing exposure and potentially leading to lifesaving actions (7). Although such transmission occurs offline as well (8-11), OSNs offer the potential for the rapid retransmission of short messages with higher fidelity-and to more persons-than would typically be feasible via other means.In addition to enabling message diffusion, the clustered structure of most OSNs (12, 13) allows retransmission to expose individuals to the same message multiple times. Multiple exposures to messages have been linked to greater confidence in message veracity (14,15), which can lead to further sharing (16,17). Repeated exposures from multiple network ties are often a prerequisite for the spread of information through networks, and are of particular importance for inducing behavioral change (4,(18)(19)(20). Under conditions of imminent threat, exposure to a warning message from a trusted source (such as a neighbor, friend, or family member) strongly affects one's ...

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Section: Message Contentmentioning

confidence: 99%

Section: Message Stylementioning

confidence: 99%

A cross-hazard analysis of terse message retransmission on Twitter

Sutton

Gibson

Phillips

et al. 2015

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

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“…The second set will explore only the original set of tweets (see RQ3a and RQ3b) and the third set only the retweets (see RQ4a and RQ4b). If different conclusions are drawn from analysing RQ2 vs both RQ3 and RQ4, then this would offer supportive empirical evidence of the importance of segmenting tweets into original tweets and retweets as suggested by the literature (Suh et al, 2010;Wright, 2009;Zhu et al, 2011;Nagarajan et al, 2010;Zhunchen et al, 2013).…”

Section: Research Question Developmentmentioning

confidence: 71%

“…Factors which trigger a retweet are diverse, ranging from the content of the tweet, the author's online profile, source of the original tweet, time of posting and number of friends in the network (see Zhunchen et al (2013) for a more detailed discussion). Zhu et al (2011) found that determining the characteristics of a retweet during a natural disaster helped the authorities to maximise information diffusion to try and reach those affected. From a marketing perspective, Nagarajan et al (2010) argue that the notion of a retweet is very important for diffusion of content through viral marketing, while Zhunchen et al (2013) state the understanding of who will share posts through retweets is of much interest to media organisations.…”

Section: The Twitter "Retweet" Concept As An Extension To Sentimentmentioning

confidence: 99%

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Examining the existence of double jeopardy and negative double jeopardy within Twitter

Rogers

Daunt

Morgan

et al. 2017

EJM

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Purpose The theory of double jeopardy (DJ) is shown to hold across broad ranging geographies and physical product categories. However, there is very little research appertaining to the subject within an online environment. In particular, studies that investigate the presence of DJ and the contrasting view point to DJ, namely, that of negative double jeopardy (NDJ), are lacking. This study aims to contribute to this identified research gap and examines the presence of DJ and NDJ within a product category, utilising data from Twitter. Design/methodology/approach A total of 354,676 tweets are scraped from Twitter and their sentiment analysed and allocated into positive, negative and no-opinion clusters using fuzzy c-means clustering. The sentiment is then compared to the market share of brands within the beer product category to establish whether a DJ or NDJ effect is present. Findings Data reveal an NDJ effect with regards to original tweets (i.e. tweets which have not been retweeted). That is, when analysing tweets relating to brands within a defined beer category, the authors find that larger brands suffer by having an increased negativity amongst the larger proportion of tweets associated with them. Research limitations/implications The clustering approach to analyse sentiment in Twitter data brings a new direction to analysis of such sentiment. Future consideration of different numbers of clusters may further the insights this form of analysis can bring to the DJ/NDJ phenomenon. Managerial implications discuss the uncovered practitioner’s paradox of NDJ and strategies for dealing with DJ and NDJ effects. Originality/value This study is the first to explore the presence of DJ and NDJ through the utilisation of sentiment analysis-derived data and fuzzy clustering. DJ and NDJ are under-explored constructs in the online environment. Typically, past research examines DJ and NDJ in separate and detached fashions. Thus, the study is of theoretical value because it outlines boundaries to the DJ and NDJ conditions. Second, this research is the first study to analyse the sentiment of consumer-authored tweets to explore DJ and NDJ effects. Finally, the current study offers valuable insight into the DJ and NDJ effects for practicing marketing managers.

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