COVID-19: The Information Warfare Paradigm Shift

• URL: http://arxiv.org/abs/2009.01267v1
• Date: Wed, 2 Sep 2020 18:04:00 GMT
• Title: COVID-19: The Information Warfare Paradigm Shift
• Authors: Jan Kallberg, Rosemary A. Burk, and Bhavani Thuraisingham
• Abstract summary: In information warfare, recent years studies and government lines of efforts have been to engage fake news, electoral interference, and fight extremist social media as the primary combat theater in the information space. The COVID-19 pandemic generates a rebuttal of these assumptions. What we have seen with COVID-19, as an indicator, is that what is related to public health is far more powerful to swing public sentiment and create reactions within the citizenry that are trigger impact at a larger magnitude that has rippled through society in multiple directions.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In Kuhn's The Structure of Scientific Revolutions, the critical term is paradigm-shift when it suddenly becomes evident that earlier assumptions no longer are correct and the plurality of the scientific community that studies this domain accepts the change. These types of events can be scientific findings or as in social science system shock that creates a punctured equilibrium that sets the stage in the developments. In information warfare, recent years studies and government lines of efforts have been to engage fake news, electoral interference, and fight extremist social media as the primary combat theater in the information space, and the tools to influence a targeted audience. The COVID-19 pandemic generates a rebuttal of these assumptions. Even if fake news and extremist social media content may exploit fault lines in our society and create a civil disturbance, tensions between federal and local government, and massive protests, it is still effects that impact a part of the population. What we have seen with COVID-19, as an indicator, is that what is related to public health is far more powerful to swing public sentiment and create reactions within the citizenry that are trigger impact at a larger magnitude that has rippled through society in multiple directions.

Related papers

• Causal Modeling of Climate Activism on Reddit [4.999814847776098]
  We develop a comprehensive causal model of how and why Reddit users engage with activist communities driving mass climate protests. We find that among users interested in climate change, participation in online activist communities is indeed influenced by direct interactions with activists. Among people aware of climate change, left-leaning people from lower socioeconomic backgrounds are particularly represented in online activist groups.
  arXiv  Detail & Related papers  (2024-10-14T14:41:09Z)
• The Morbid Realities of Social Media: An Investigation into the Misinformation Shared by the Deceased Victims of COVID-19 [0.4995343972237368]
  We study a unique dataset of Facebook posts by users who shared and believed in Covid-19 misinformation before succumbing to Covid-19 often resulting in death. Our analysis reveals the overwhelming politicization of Covid-19 through the prevalence of anti-government themes. Results from this study bring insights into the responsibility of political elites in shaping public discourse and the platform's role in dampening the reach of harmful misinformation.
  arXiv  Detail & Related papers  (2022-09-20T19:47:27Z)
• Adherence to Misinformation on Social Media Through Socio-Cognitive and Group-Based Processes [79.79659145328856]
  We argue that when misinformation proliferates, this happens because the social media environment enables adherence to misinformation. We make the case that polarization and misinformation adherence are closely tied.
  arXiv  Detail & Related papers  (2022-06-30T12:34:24Z)
• "COVID-19 was a FIFA conspiracy #curropt": An Investigation into the Viral Spread of COVID-19 Misinformation [60.268682953952506]
  We estimate the extent to which misinformation has influenced the course of the COVID-19 pandemic using natural language processing models. We provide a strategy to combat social media posts that are likely to cause widespread harm.
  arXiv  Detail & Related papers  (2022-06-12T19:41:01Z)
• Impact of COVID-19 Policies and Misinformation on Social Unrest [0.0]
  We focus on the interplay between social unrest (protests), health outcomes, public health orders, and misinformation in eight countries of Western Europe and four regions of the United States. We created 1-3 week forecasts of both a binary protest metric for identifying times of high protest activity and the overall protest counts over time. We found that for all regions, except Belgium, at least one feature from our various data streams was predictive of protests.
  arXiv  Detail & Related papers  (2021-10-07T16:05:10Z)
• ExcavatorCovid: Extracting Events and Relations from Text Corpora for Temporal and Causal Analysis for COVID-19 [63.72766553648224]
  ExcavatorCovid is a machine reading system that ingests open-source text documents. It extracts COVID19 related events and relations between them, and builds a Temporal and Causal Analysis Graph.
  arXiv  Detail & Related papers  (2021-05-05T01:18:46Z)
• Misinfo Belief Frames: A Case Study on Covid & Climate News [49.979419711713795]
  We propose a formalism for understanding how readers perceive the reliability of news and the impact of misinformation. We introduce the Misinfo Belief Frames (MBF) corpus, a dataset of 66k inferences over 23.5k headlines. Our results using large-scale language modeling to predict misinformation frames show that machine-generated inferences can influence readers' trust in news headlines.
  arXiv  Detail & Related papers  (2021-04-18T09:50:11Z)
• Pandemic Pulse: Unraveling and Modeling Social Signals during the COVID-19 Pandemic [12.050597862123313]
  We present and begin to explore a collection of social data that represents part of the COVID-19 pandemic's effects on the United States. This data is collected from a range of sources and includes longitudinal trends of news topics, social distancing behaviors, community mobility changes, web searches, and more.
  arXiv  Detail & Related papers  (2020-06-10T17:55:44Z)
• Analysis of misinformation during the COVID-19 outbreak in China: cultural, social and political entanglements [6.256108383411306]
  COVID-19 resulted in an infodemic, which could erode public trust, impede virus containment, and outlive the pandemic itself. The evolving and fragmented media landscape is a key driver of the spread of misinformation. Our findings shed light on the distinct characteristics of misinformation during the COVID-19 and offer insights into combating misinformation in China and across the world at large.
  arXiv  Detail & Related papers  (2020-05-21T01:34:08Z)
• The Ivory Tower Lost: How College Students Respond Differently than the General Public to the COVID-19 Pandemic [66.80677233314002]
  Pandemic of the novel Coronavirus Disease 2019 (COVID-19) has presented governments with ultimate challenges. In the United States, the country with the highest confirmed COVID-19 infection cases, a nationwide social distancing protocol has been implemented by the President. This paper aims to discover the social implications of this unprecedented disruption in our interactive society by mining people's opinions on social media.
  arXiv  Detail & Related papers  (2020-04-21T13:02:38Z)
• Echo Chambers on Social Media: A comparative analysis [64.2256216637683]
  We introduce an operational definition of echo chambers and perform a massive comparative analysis on 1B pieces of contents produced by 1M users on four social media platforms. We infer the leaning of users about controversial topics and reconstruct their interaction networks by analyzing different features. We find support for the hypothesis that platforms implementing news feed algorithms like Facebook may elicit the emergence of echo-chambers.
  arXiv  Detail & Related papers  (2020-04-20T20:00:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.