How resilient is the Open Web to the COVID-19 pandemic?

• URL: http://arxiv.org/abs/2107.14534v3
• Date: Mon, 28 Mar 2022 10:01:44 GMT
• Title: How resilient is the Open Web to the COVID-19 pandemic?
• Authors: Jos\'e Gonz\'alez-Caba\~nas, Patricia Callejo, Pelayo Vallina, \'Angel Cuevas, Rub\'en Cuevas, Antonio Fern\'andez Anta
• Abstract summary: Despite its importance for society, it is unknown how the COVID-19 pandemic is affecting the Open Web. We study the impact of the pandemic in the financial backbone of the Open Web, the online advertising business. We analyze the distribution of the Open Web composition across business categories and its evolution during the COVID-19 pandemic.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In this paper we refer to the Open Web to the set of services offered freely to Internet users, representing a pillar of modern societies. Despite its importance for society, it is unknown how the COVID-19 pandemic is affecting the Open Web. In this paper, we address this issue, focusing our analysis on Spain, one of the countries which have been most impacted by the pandemic. On the one hand, we study the impact of the pandemic in the financial backbone of the Open Web, the online advertising business. To this end, we leverage concepts from Supply-Demand economic theory to perform a careful analysis of the elasticity in the supply of ad-spaces to the financial shortage of the online advertising business and its subsequent reduction in ad spaces' price. On the other hand, we analyze the distribution of the Open Web composition across business categories and its evolution during the COVID-19 pandemic. These analyses are conducted between Jan 1st and Dec 31st, 2020, using a reference dataset comprising information from more than 18 billion ad spaces. Our results indicate that the Open Web has experienced a moderate shift in its composition across business categories. However, this change is not produced by the financial shortage of the online advertising business, because as our analysis shows, the Open Web's supply of ad spaces is inelastic (i.e., insensitive) to the sustained low-price of ad spaces during the pandemic. Instead, existing evidence suggests that the reported shift in the Open Web composition is likely due to the change in the users' online behavior (e.g., browsing and mobile apps utilization patterns).

Related papers

• Online Advertising is a Regrettable Necessity: On the Dangers of Pay-Walling the Web [0.0]
  We show that 135 countries with a total population estimate of 6.56 billion people cannot afford a scenario of a fully paywalled web. We call for further research and policy initiatives to keep the web open and more inclusive with a sustainable business model.
  arXiv  Detail & Related papers  (2024-08-17T03:23:08Z)
• Web3: The Next Internet Revolution [50.16560061003771]
  Next internet revolution: Web3 is going to open new opportunities for traditional social models. Decentralized finance will be global, and open with financial inclusiveness for unbanked people. Several worthwhile future research directions of Web3 are discussed.
  arXiv  Detail & Related papers  (2023-03-22T23:37:43Z)
• "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)
• Macroscopic properties of buyer-seller networks in online marketplaces [55.41644538483948]
  We analyze two datasets containing 245M transactions that took place on online marketplaces between 2010 and 2021. We show that transactions in online marketplaces exhibit strikingly similar patterns despite significant differences in language, lifetimes, products, regulation, and technology.
  arXiv  Detail & Related papers  (2021-12-16T18:00:47Z)
• Debate on Online Social Networks at the Time of COVID-19: An Italian Case Study [4.176752121302988]
  We analyze how the interaction patterns around popular influencers in Italy changed during the first six months of 2020. We collected a large dataset for this group of public figures, including more than 54 million comments on over 140 thousand posts. We also analyze the user sentiment through the psycholinguistic properties of comments, and the results testified the rapid boom and disappearance of topics related to the pandemic.
  arXiv  Detail & Related papers  (2021-06-02T08:25:19Z)
• Learning to Infer User Hidden States for Online Sequential Advertising [52.169666997331724]
  We propose our Deep Intents Sequential Advertising (DISA) method to address these issues. The key part of interpretability is to understand a consumer's purchase intent which is, however, unobservable (called hidden states)
  arXiv  Detail & Related papers  (2020-09-03T05:12:26Z)
• Dark Web Marketplaces and COVID-19: before the vaccine [53.447910186085586]
  We analyse 851,199 listings extracted from 30 dark web marketplaces between January 1, 2020 and November 16, 2020. We identify 788 listings directly related to COVID-19 products and monitor the temporal evolution of product categories. We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs.
  arXiv  Detail & Related papers  (2020-08-04T14:27:41Z)
• On Analyzing Antisocial Behaviors Amid COVID-19 Pandemic [5.900114841365645]
  Despite the gravity of the issue, very few studies have studied online antisocial behaviors amid the COVID-19 pandemic. In this paper, we fill the research gap by collecting and annotating a large dataset of over 40 million COVID-19 related tweets. We also conduct an empirical analysis of our annotated dataset and found that new abusive lexicons are introduced amid the COVID-19 pandemic.
  arXiv  Detail & Related papers  (2020-07-21T11:11:35Z)
• 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)
• Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions [1.6571886312953874]
  An estimated 2.95 billion people in 2019 used social media worldwide. The widespread of the Coronavirus COVID-19 resulted with a tsunami of social media. This paper presents a large-scale study based on data mined from Twitter.
  arXiv  Detail & Related papers  (2020-05-18T15:53:13Z)
• When Wireless Communication Faces COVID-19: Combating the Pandemic and Saving the Economy [93.08344893433639]
  The year 2020 is experiencing a global health and economic crisis due to the COVID-19 pandemic. Countries across the world are using digital technologies to fight this global crisis. We show how these technologies are helping to combat this pandemic, including monitoring of the virus spread. We discuss the challenges faced by wireless technologies, including privacy, security, and misinformation.
  arXiv  Detail & Related papers  (2020-05-12T12:27:29Z)

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.