Leveraging Market Power Through Tying: Does Google Behave Anti-Competitively?
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Google Ad Tech
Yaletap University Thurman Arnold Project Digital Platform Theories of Harm Paper Series: 4 Report on Google’s Conduct in Advertising Technology May 2020 Lissa Kryska Patrick Monaghan I. Introduction Traditional advertisements appear in newspapers and magazines, on television and the radio, and on daily commutes through highway billboards and public transportation signage. Digital ads, while similar, are powerful because they are tailored to suit individual interests and go with us everywhere: the bookshelf you thought about buying two days ago can follow you through your favorite newspaper, social media feed, and your cousin’s recipe blog. Digital ads also display in internet search results, email inboxes, and video content, making them truly ubiquitous. Just as with a full-page magazine ad, publishers rely on the revenues generated by selling this ad space, and the advertiser relies on a portion of prospective customers clicking through to finally buy that bookshelf. Like any market, digital advertising requires the matching of buyers (advertisers) and sellers (publishers), and the intermediaries facilitating such matches have more to gain every year: A PwC report estimated that revenues for internet advertising totaled $57.9 billion for 2019 Q1 and Q2, up 17% over the same half-year period in 2018.1 Google is the dominant player among these intermediaries, estimated to have netted 73% of US search ad spending2 and 37% of total US digital ad spending3 in 2019. Such market concentration prompts reasonable questions about whether customers are losing out on some combination of price, quality, and innovation. This report will review the significant 1 PricewaterhouseCoopers for IAB (October 2019), Internet Advertising Revenue Report: 2019 First Six Months Results, p.2. -
A Longitudinal Study of Google Play App Actual Installations
1 A Longitudinal Study of Google Play Rahul Potharaju∗, Mizanur Rahman†, Bogdan Carbunar† ∗Cloud and Information Services Lab, Microsoft †Florida International University Abstract—The difficulty of large scale monitoring of app to use app markets as a launch pad for their malware [26], markets affects our understanding of their dynamics. This is [28], [33], [20]. particularly true for dimensions such as app update frequency, Contributions. In this article we seek to shed light on the control and pricing, the impact of developer actions on app popularity, as well as coveted membership in top app lists. In this dynamics of Google Play, the most popular Android app paper we perform a detailed temporal analysis on two datasets market. We report results from one of the first characteristic we have collected from the Google Play Store, one consisting studies on Google Play, using real-world time series data. To of 160,000 apps and the other of 87,223 newly released apps. this end, we have developed iMarket, a prototype app market We have monitored and collected data about these apps over crawling system. We have used iMarket to collect data from more than 6 months. Our results show that a high number of these apps have not been updated over the monitoring interval. more than 470,000 Google Play apps, and daily monitor more Moreover, these apps are controlled by a few developers that than 160,000 apps, over more than 6 months. dominate the total number of app downloads. We observe that We use this data to study two key aspects of Google Play. -
Privacy Policy Interpretation and Definitions
Privacy Policy This Privacy Policy describes Our policies and procedures on the collection, use and disclosure of Your information when You use the Service and tells You about Your privacy rights and how the law protects You. We use Your Personal data to provide and improve the Service. By using the Service, You agree to the collection and use of information in accordance with this Privacy Policy. Interpretation and Definitions Interpretation The words of which the initial letter is capitalized have meanings defined under the following conditions. The following definitions shall have the same meaning regardless of whether they appear in singular or in plural. Definitions For the purposes of this Privacy Policy: • You means the individual accessing or using the Service, or the company, or other legal entity on behalf of which such individual is accessing or using the Service, as applicable. Under GDPR (General Data Protection Regulation), You can be referred to as the Data Subject or as the User as you are the individual using the Service. • Company (referred to as either "the Company", "We", "Us" or "Our" in this Agreement) refers to Adventure City Inc., 1238 S. BEACH BLVD., SUITE E. For the purpose of the GDPR, the Company is the Data Controller. • Affiliate means an entity that controls, is controlled by or is under common control with a party, where "control" means ownership of 50% or more of the shares, equity interest or other securities entitled to vote for election of directors or other managing authority. • Account means a unique account created for You to access our Service or parts of our Service. -
Corpora: Google Ngram Viewer and the Corpus of Historical American English
EuroAmerican Journal of Applied Linguistics and Languages E JournALL Volume 1, Issue 1, November 2014, pages 48 68 ISSN 2376 905X DOI - - www.e journall.org- http://dx.doi.org/10.21283/2376905X.1.4 - Exploring mega-corpora: Google Ngram Viewer and the Corpus of Historical American English ERIC FRIGINALa1, MARSHA WALKERb, JANET BETH RANDALLc aDepartment of Applied Linguistics and ESL, Georgia State University bLanguage Institute, Georgia Institute of Technology cAmerican Language Institute, New York University, Tokyo Received 10 December 2013; received in revised form 17 May 2014; accepted 8 August 2014 ABSTRACT EN The creation of internet-based mega-corpora such as the Corpus of Contemporary American English (COCA), the Corpus of Historical American English (COHA) (Davies, 2011a) and the Google Ngram Viewer (Cohen, 2010) signals a new phase in corpus-based research that provides both novice and expert researchers immediate access to a variety of online texts and time-coded data. This paper explores the applications of these corpora in the analysis of academic word lists, in particular, Coxhead’s (2000) Academic Word List (AWL). Coxhead (2011) has called for further research on the AWL with larger corpora, noting that learners’ use of academic vocabulary needs to address for the AWL to be useful in various contexts. Results show that words on the AWL are declining in overall frequency from 1990 to the present. Implications about the AWL and future directions in corpus-based research utilizing mega-corpora are discussed. Keywords: GOOGLE N-GRAM VIEWER, CORPUS OF HISTORICAL AMERICAN ENGLISH, MEGA-CORPORA, TREND STUDIES. ES La creación de megacorpus basados en Internet, tales como el Corpus of Contemporary American English (COCA), el Corpus of Historical American English (COHA) (Davies, 2011a) y el Visor de Ngramas de Google (Cohen, 2010), anuncian una nueva fase en la investigación basada en corpus, pues proporcionan, tanto a investigadores noveles como a expertos, un acceso inmediato a una gran diversidad de textos online y datos codificados con time-code. -
Empirical Study on Media Monitoring and Internationalisation Resources
MULTISENSOR Mining and Understanding of multilinguaL contenT for Intelligent Sentiment Enriched coNtext and Social Oriented inteRpretation FP7-610411 D2.1 Empirical study on media monitoring and internationalisation resources Dissemination level: Public Contractual date of delivery: Month 6, 30 April 2014 Actual date of delivery: Month 6, 30 April 2014 Workpackage: WP2 Multilingual and multimedia content extraction Task: T2.1 Empirical study Type: Report Approval Status: Final Draft Version: 1.1 Number of pages: 172 Filename: D2.1_EmpiricalStudy_2014-04-30_v1.1.pdf Abstract This empirical study identifies the resources and the type of information that needs to be extracted in the project and their encoding types. In addition it reports information retrieval and crawling techniques that could be employed for the extraction of this information. The information in this document reflects only the author’s views and the European Community is not liable for any use that may be made of the information contained therein. The information in this document is provided as is and no guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. Page 1 Co-funded by the European Union Page 2 D2.1 – V1.1 History Version Date Reason Revised by 0.1 20/03/2014 Draft V. Aleksić (LT) 0.2 03/04/2014 Comments S. Vrochidis (CERTH), I. Arapakis (BM-Y!) 0.3 15/04/2014 Update V.Aleksić (LT) 0.4 16/04/2014 Document for internal review V.Aleksić (LT) 0.5 24/04/2014 Review A. -
Copyright Reform in the EU: Grappling with the Google Effect
Copyright Reform in the EU: Grappling with the Google Effect Annemarie Bridy Sweeping changes are coming to copyright law in the European Union. Following four years of negotiations, the European Parliament in April 2019 approved the final text of the Digital Single Market Directive (DSMD).1 EU member states now have two years to transpose its provisions intodomestic law. The new directive, which is the most substantial change to EU copyright law in a generation, contains provisions for enhancing cross-border access to content available through digital subscription services, enabling new uses of copyrighted works for education and research, and, most controversially, ‘clarifying’ the role of online services in the distribution of copyrighted works. The provisions associated with the last of these goals—Article 15 (the ‘link tax’) and Article 17 (‘upload filters’) take aim directly at two services operated by Google: Google News and YouTube. Article 15 is intended to provide remuneration for press publishers when snippets of their articles are displayed by search engines and news aggregators.2 Article 17, which this article takes for its subject, is intended to address the so-called ‘value gap’—the music industry’s longstanding complaint that YouTube undercompensates music rightholders for streams of user videos containing claimed copyrighted content.3 The text of the DSMD nowhere mentions YouTube, but anyone versed in the political economy of digital copyright knows that Article 17 was purpose-built to make YouTube pay. The important questions to ask in the wake of Article 17 are who else will pay—and in what ways. This article offers a focused examination of Article 17 as public law created to settle a private score between the music industry and YouTube. -
4. Google Health a Number of Companies Offer to Store Personal
4. Google Health A number of companies offer to store personal health records on the Web. Companies in this business hope to capitalize on the huge market of interested consumers seeking online health information and controlled health spending. The newest entry is Google Health with its technical know-how, deep pockets, and familiarity to consumers. A trial of Google's program with Cleveland Clinic patients was quickly oversubscribed, quelling fears that patients would worry about the security of their records. Google Health users will create their own electronic medical record online, with the capability to enter and manage health information and access it online from anywhere. This portable medical record will be accessible regardless of doctor, moves, insurance changes, etc. The record can be set to send reminders to refill prescriptions and schedule return medical visits. Permission from the patient is required to access the patient's record; however, there are important exceptions noted in the Google Health Terms of Service and Sharing Authorization to which users must agree when they sign on for the service. Google Health is free to users. Experts have long touted electronic medical records as a way to overcome the lack of coordination among health care providers. In addition, electronic records provide patients and providers with search capability linking information in the patient's records with information about health care alternatives, thereby giving patients more control over their health care choices. Access is available to patients, and to providers with patient consent. Google Health allows the patient to determine what information is shared with medical providers and pharmacies. -
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1 TABLE OF CONTENTS 2 I. INTRODUCTION ...................................................................................................... 2 3 II. JURISDICTION AND VENUE ................................................................................. 8 4 III. PARTIES .................................................................................................................... 9 5 A. Plaintiffs .......................................................................................................... 9 6 B. Defendants ....................................................................................................... 9 7 IV. FACTUAL ALLEGATIONS ................................................................................... 17 8 A. Alphabet’s Reputation as a “Good” Company is Key to Recruiting Valuable Employees and Collecting the User Data that Powers Its 9 Products ......................................................................................................... 17 10 B. Defendants Breached their Fiduciary Duties by Protecting and Rewarding Male Harassers ............................................................................ 19 11 1. The Board Has Allowed a Culture Hostile to Women to Fester 12 for Years ............................................................................................. 19 13 a) Sex Discrimination in Pay and Promotions: ........................... 20 14 b) Sex Stereotyping and Sexual Harassment: .............................. 23 15 2. The New York Times Reveals the Board’s Pattern -
Between Enforcement and Regulation
Katharina Voss Between Enforcement and Regulation A Study of the System of Case Resolution Mechanisms Used by the Between Enforcement and Regulation Between European Commission in the Enforcement of Articles 101 and 102 TFEU Katharina Voss ISBN 978-91-7797-570-0 Department of Law Doctoral Thesis in European Law at Stockholm University, Sweden 2019 Between Enforcement and Regulation A Study of the System of Case Resolution Mechanisms Used by the European Commission in the Enforcement of Articles 101 and 102 TFEU Katharina Voss Academic dissertation for the Degree of Doctor of Laws in European Law at Stockholm University to be publicly defended on Friday 12 April 2019 at 10.00 in Nordenskiöldsalen, Geovetenskapens hus, Svante Arrhenius väg 12. Abstract This thesis examines the current design of the system of case resolution mechanisms used by the European Commission (the Commission) where an infringement of Articles 101 and 102 TFEU is suspected and advances some proposals regarding this design. Infringements of Articles 101 and 102 TFEU cause considerable damage to the EU economy and ultimately, to consumers. Despite intensified enforcement of Articles 101 and 102 TFEU and ever-growing fines imposed for such infringements, the Commission continues to discover new infringements, which indicates a widespread non-compliance with EU competition rules. This raises the question of whether the enforcement currently carried out by the Commission is suitable for achieving compliance with Articles 101 and 102 TFEU. The thesis is divided into four main parts: First, the objectives pursued by the system of case resolution mechanisms used by the Commission are identified. -
The Fourth Paradigm
ABOUT THE FOURTH PARADIGM This book presents the first broad look at the rapidly emerging field of data- THE FOUR intensive science, with the goal of influencing the worldwide scientific and com- puting research communities and inspiring the next generation of scientists. Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud- computing technologies. This collection of essays expands on the vision of pio- T neering computer scientist Jim Gray for a new, fourth paradigm of discovery based H PARADIGM on data-intensive science and offers insights into how it can be fully realized. “The impact of Jim Gray’s thinking is continuing to get people to think in a new way about how data and software are redefining what it means to do science.” —Bill GaTES “I often tell people working in eScience that they aren’t in this field because they are visionaries or super-intelligent—it’s because they care about science The and they are alive now. It is about technology changing the world, and science taking advantage of it, to do more and do better.” —RhyS FRANCIS, AUSTRALIAN eRESEARCH INFRASTRUCTURE COUNCIL F OURTH “One of the greatest challenges for 21st-century science is how we respond to this new era of data-intensive -
Natural Language Processing 2018 Highlights
NLP 2018 Highlights By Elvis Saravia 1 Table of Contents Introduction ............................................................................................................................................ 4 Research ................................................................................................................................................. 5 Reinforcement Learning ...................................................................................................................... 5 Sentiment Analysis and Related Topics ................................................................................................ 7 AI Ethics and Security .......................................................................................................................... 9 Clinical NLP and ML ........................................................................................................................... 12 Computer Vision ................................................................................................................................ 15 Deep Learning and Optimization ........................................................................................................ 17 Transfer Learning for NLP .................................................................................................................. 19 AI Generalization ............................................................................................................................... 20 Explainability and Interpretability -
Testimony of Marc Donner, Director of Engineering, Google Health
Testimony of Marc Donner, Director of Engineering, Google Health National Committee on Vital and Health Statistics Executive Subcommittee on Privacy, Confidentiality & Security Hearing on Personal Health Records May 20, 2009 Good afternoon and thank you for the opportunity to testify before the subcommittee on the important issue of Personal Health Records (PHRs). My name is Marc Donner and I am the Engineering Director for Google Health™. I have over thirty years of experience in engineering of hardware, software, and complex systems, and I hold a Ph.D. in Computer Science from Carnegie-Mellon University. My role on the Google Health team is to supervise the infrastructure and product design of Google Health. The focus of my attention is on ensuring our ability to scale, receive standards-compliant data from as many sources as possible, protect the integrity and privacy of PHR information, and increase the usefulness of Google Health data for our users. In my testimony today, I would like to focus on three main points: First, I'd like to discuss PHRs and their role in the healthcare industry. Second, I'll describe Google's health-related initiatives including Google Health, our own PHR product. Finally, I will make a handful of policy recommendations based on the experience that Google™ has had to date with health information technology generally and PHRs specifically. PHRs and how they fit into the bigger picture Google Health launched its PHR in the spring of 2008. In 2006, it was estimated that were roughly 200 PHRs. 1 In the past three years, many more products have emerged, along with Google’s offering.