{"title":"Big Tech Dominance Despite Global Mistrust","authors":"Hazem Ibrahim;Mikolaj Debicki;Talal Rahwan;Yasir Zaki","doi":"10.1109/TCSS.2023.3339183","DOIUrl":null,"url":null,"abstract":"The technological and online experiences of billions worldwide are dominated by a handful of companies known as “Big Tech.” Despite this being a cause for concern in governmental, economic, and ethical spheres, the literature lacks a study exploring the impact of public scandals on, and the global sentiment toward, Big Tech. Here, we quantify the power of Big Tech by analyzing their acquisitions, market capitalization, and number of monthly active users. Moreover, we utilize the synthetic control method to estimate the effect of public scandals on the stock price of two Big Tech companies, and find that they had no lasting effect. We also analyze the number of tweets mentioning these scandals, and find that they quickly fade from the spotlight. To explore public sentiment, we survey 5300 participants across 25 countries, and find that those from countries with lower digital literacy and more authoritarian regimes are more trusting of Big Tech. Furthermore, we find that one in three feels they lack control over the data collected about them, and one in four feels that Big Tech knows what they are thinking, knows more about them than their best friend, and may even be secretly listening to their conversations. Additionally, one in four feels addicted to Big Tech products, have no choice but to use them, and wishes there were more companies to choose from. These findings highlight the adverse effect of the oligopolistic nature of Big Tech on consumer choice and help inform policy-makers aiming to curb their dominance.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10379489","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10379489/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 0
Abstract
The technological and online experiences of billions worldwide are dominated by a handful of companies known as “Big Tech.” Despite this being a cause for concern in governmental, economic, and ethical spheres, the literature lacks a study exploring the impact of public scandals on, and the global sentiment toward, Big Tech. Here, we quantify the power of Big Tech by analyzing their acquisitions, market capitalization, and number of monthly active users. Moreover, we utilize the synthetic control method to estimate the effect of public scandals on the stock price of two Big Tech companies, and find that they had no lasting effect. We also analyze the number of tweets mentioning these scandals, and find that they quickly fade from the spotlight. To explore public sentiment, we survey 5300 participants across 25 countries, and find that those from countries with lower digital literacy and more authoritarian regimes are more trusting of Big Tech. Furthermore, we find that one in three feels they lack control over the data collected about them, and one in four feels that Big Tech knows what they are thinking, knows more about them than their best friend, and may even be secretly listening to their conversations. Additionally, one in four feels addicted to Big Tech products, have no choice but to use them, and wishes there were more companies to choose from. These findings highlight the adverse effect of the oligopolistic nature of Big Tech on consumer choice and help inform policy-makers aiming to curb their dominance.
期刊介绍:
IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.