Information Overload and Viral Marketing: Countermeasures and Strategies

Cheng, Jiesi; Sun, Aaron; Zeng, Daniel

doi:10.1007/978-3-642-12079-4_16

Cited by 17 publications

(10 citation statements)

References 11 publications

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“…[31][32][33][34][35] By examining the perceived levels of news overload on different delivery platforms, and by weighing factors contributing to perceptions of overload, news content producers might find stronger ways to reach and maintain consumers.…”

Section: Limitations and Conclusionmentioning

confidence: 99%

News and the Overloaded Consumer: Factors Influencing Information Overload Among News Consumers

Holton

Chyi

2012

Cyberpsychology, Behavior, and Social Networking

126

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Section: Limitations and Conclusionmentioning

confidence: 99%

News and the Overloaded Consumer: Factors Influencing Information Overload Among News Consumers

Holton

Chyi

2012

Cyberpsychology, Behavior, and Social Networking

126

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“…Regarding social media, some research results show that information overload on social media negatively affect organization management (Hemp, 2009;Tarafdar et al, 2010Tarafdar et al, , 2011Maier et al, 2012;Bucher et al, 2013). In the context of marketing, researchers have been accumulating empirical data on how the contagion of information on social media by general users is affected by users' information overload (Cheng et al, 2010;Lerman, 2012, 2014).…”

Section: Information Overloadmentioning

confidence: 96%

The anatomy of tweet overload: How number of tweets received, number of friends, and egocentric network density affect perceived information overload

Sasaki

Kawai

Kitamura

2015

Telematics and Informatics

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“…Cheng, et al [52] proposed a method of diffusion which takes IO and its countermeasures into account. The models may give a more precise and dynamic description of the information dissemination processes by eliminating the "one-message-on-time" constraint.…”

Section: ) Management Of Iomentioning

confidence: 99%

Solution for Information Overload Using Faceted Search–A Review

et al. 2020

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In the modern society, Internet provides massive amounts of heterogeneous information, hence Information overload has become an ubiquitous issue. In this paper, we conduct a large scale quantitative study for articles dealing with (1) information overloading; (2) faceted search; and (3) filtering the data in three major databases, namely, Web of Science, ScienceDirect, and IEEE Explore. These three databases have presented 172 articles, which can be classified into four categories. The first category contains review and survey papers related to information overload. The second category includes papers that concentrate on developing theoretical frameworks to reduce information overloading. The third category contains papers dealing with improving structure or architectural of software for filtering the huge data. The fourth category includes papers that provide criteria to evaluate filtering techniques. Finally, our contribution provides further understanding of information overload, and gives an important basis for future research. Moreover, we illustrate that the dynamic faceted filters are more efficient to reduce the information overload.

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Information Overload and Viral Marketing: Countermeasures and Strategies

Cited by 17 publications

References 11 publications

News and the Overloaded Consumer: Factors Influencing Information Overload Among News Consumers

News and the Overloaded Consumer: Factors Influencing Information Overload Among News Consumers

The anatomy of tweet overload: How number of tweets received, number of friends, and egocentric network density affect perceived information overload

Solution for Information Overload Using Faceted Search–A Review

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