Understanding the Personality of Contributors to Information Cascades in Social Media in Response to the COVID-19 Pandemic

Power of social media including Twitter for English speaking community to shape public opinion becomes critical during the current pandemic because of misinformation. The existing studies on spreading misinformation on social media hypothesise that the initial message is fake. In contrast, we focus on information distortion occurring in cascades as the initial message about the Covid-19 treatment is quoted or receives a reply. Public persons discuss medical information on Twitter providing fast and simple response to complex medical problems that users find very attractive to follow. Followers generate information cascades while quoting and commenting on the initial message. In the cascades, medical information from the initial tweet is often distorted. The discussion of the Covid-19 treatment in the cascades is politicized according to users’ political sympathies. We show a significant information shift in cascades initiated by public figures during the Covid-19 pandemic. The study provide valuable insights for the semantic analysis of information distortion.

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Information cascades in social media in response to a crisis

Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion ◽

10.1145/2187980.2188173 ◽

2012 ◽

Cited By ~ 25

Author(s):

Cindy Hui ◽

Yulia Tyshchuk ◽

William A. Wallace ◽

Malik Magdon-Ismail ◽

Mark Goldberg

Keyword(s):

Social Media ◽

Information Cascades

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How consumers react to woke advertising: methodological triangulation based on social media data and self-report data

Journal of Research in Interactive Marketing ◽

10.1108/jrim-09-2020-0185 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Yang Feng ◽

Huan Chen ◽

Ho-Young (Anthony) Ahn

Keyword(s):

Social Media ◽

Social Norms ◽

Social Norm ◽

Self Report ◽

Information Cascades ◽

Content Type ◽

Consumer Responses ◽

Methodological Triangulation ◽

Information Sets ◽

Self Report Data

Purpose Guided by a synthesis of social norms theory (SNT), the social identity model of deindividuation effects (SIDE) and information cascades theory (ICT), this study aims to unveil the mechanism underlying the role of social norms in shaping consumer responses to woke advertising in the algorithmic social media environment. Design/methodology/approach This paper analyzed 125,481 unique comments on a woke campaign, which represented the dynamic social norms condition in which the prominence of popularity information sets a social norm that can be passed on through a sequential commenting process. Also, this paper conducted an experiment with two conditions, namely, static social norms condition, representing a situation in which the prominence of popularity information sets a social norm through a non-sequential commenting process; without social norms condition, epitomizing the situation in which there is no popularity information that can set a social norm. Findings The results revealed that when evaluating a social media-based woke ad, depersonalized consumers in a dynamic social norms condition were more likely to be influenced by the prevailing norms than those in a static social norms condition were. Originality/value Through the lens of ICT, this research extends SNT and SIDE by detailing the procedure regarding how perceived social norms shape the formation of consumer opinions in a sequential fashion.

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The Impact of Artificial Intelligence on Branding

Journal of Global Information Management ◽

10.4018/jgim.20210701.oa10 ◽

2021 ◽

Vol 29 (4) ◽

pp. 221-246

Author(s):

Varsha P. S. ◽

Shahriar Akter ◽

Amit Kumar ◽

Saikat Gochhait ◽

Basanna Patagundi

Keyword(s):

Artificial Intelligence ◽

Social Media ◽

Citation Analysis ◽

Brand Choice ◽

Media Analysis ◽

Social Media Analytics ◽

Information Cascades ◽

Luxury Brands ◽

Value Propositions ◽

The Impact

Understanding the growth paths of artificial intelligence (AI) and its impact on branding is extremely pertinent of technology-driven marketing. This explorative research covers a complete bibliometric analysis of the impact of AI on branding. The sample for this research included all 117 articles from the period of 1982-2019 in the Scopus database. A bibliometric study was conducted using co-occurrence, citation analysis and co-citation analysis. The empirical analysis investigates the value propositions of AI on branding. The study revealed the nine clusters of co-occurrence: Social Media Analytics and Brand Equity; Neural Networks and Brand Choice; Chat Bots-Brand Intimacy; Twitter, Facebook, Instagram-Luxury Brands; Interactive Agent-Brand Love and User Choice; Algorithm Recommendations and E-Brand Experience; User-Generated Content-Brand Sustainability; Brand Intelligence Analytics; and Digital Innovations and Brand Excellence. The findings also identify four clusters of citation analysis—Social Media Analysis and Brand Photos, Network Analysis and E-Commerce, Hybrid Simulating Modelling, and Real-time Knowledge-Based Systems—and four clusters of co-citation analysis: B2B Technology Brands, AI Fostered E-Brands, Information Cascades and Online Brand Ratings, and Voice Assistants-Brand Eureka Moments. Overall, the study presents the patterns of convergence and divergence of themes, narrowing to the specific topic, and multidisciplinary engagement in research, thus offering the recent insights in the field of AI on branding.

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Inferring mechanisms of response prioritization on social media under information overload

Scientific Reports ◽

10.1038/s41598-020-79897-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Chathika Gunaratne ◽

William Rand ◽

Ivan Garibay

Keyword(s):

Social Media ◽

Information Overload ◽

User Interaction ◽

Evolutionary Model ◽

Online Information ◽

Information Cascades ◽

Agent Based Model ◽

Agent Based ◽

Highly Active ◽

Online Social Media

AbstractHuman decision-making is subject to the biological limits of cognition. The fluidity of information propagation over online social media often leads users to experience information overload. This in turn affects which information received by users are processed and gain a response to, imposing constraints on volumes of, and participation in, information cascades. In this study, we investigate properties contributing to the visibility of online social media notifications by highly active users experiencing information overload via cross-platform social influence. We analyze simulations of a coupled agent-based model of information overload and the multi-action cascade model of conversation with evolutionary model discovery. Evolutionary model discovery automates mechanistic inference on agent-based models by enabling random forest importance analysis on genetically programmed agent-based model rules. The mechanisms of information overload have shown to contribute to a multitude of global properties of online information cascades. We investigate nine characteristics of online messages that may contribute to the prioritization of messages for response. Our results indicate that recency had the largest contribution to message visibility, with individuals prioritizing more recent notifications. Global popularity of the conversation originator had the second highest contribution, and reduced message visibility. Messages that presented opportunity for novel user interaction, yet high reciprocity showed to have relatively moderate contribution to message visibility. Finally, insights from the evolutionary model discovery results helped inform response prioritization rules, which improved the robustness and accuracy of the model of information overload.

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Where Social Media Meets AAC

ASHA Leader ◽

10.1044/leader.gs.20072015.np ◽

2015 ◽

Vol 20 (7) ◽

Author(s):

Vicki Clarke

Keyword(s):

Social Media

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Social Media: A Powerful Tool for AAC Learning and Networking

ASHA Leader ◽

10.1044/leader.gs.22022017.np ◽

2017 ◽

Vol 22 (2) ◽

Author(s):

Lauren Enders

Keyword(s):

Social Media

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Making Twitter Work For You

ASHA Leader ◽

10.1044/leader.stw.18052013.np ◽

2013 ◽

Vol 18 (5) ◽

Keyword(s):

Social Media ◽

Public Relations ◽

Speech Language Pathologists

As professionals who recognize and value the power and important of communications, audiologists and speech-language pathologists are perfectly positioned to leverage social media for public relations.

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