Notes for the Central Tables of the Book, Predictive Analytics: the Power to Predict Who Will Click, Buy, Lie, Or Die — Revised and Updated Edition
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Deepfakes and Cheap Fakes
DEEPFAKES AND CHEAP FAKES THE MANIPULATION OF AUDIO AND VISUAL EVIDENCE Britt Paris Joan Donovan DEEPFAKES AND CHEAP FAKES - 1 - CONTENTS 02 Executive Summary 05 Introduction 10 Cheap Fakes/Deepfakes: A Spectrum 17 The Politics of Evidence 23 Cheap Fakes on Social Media 25 Photoshopping 27 Lookalikes 28 Recontextualizing 30 Speeding and Slowing 33 Deepfakes Present and Future 35 Virtual Performances 35 Face Swapping 38 Lip-synching and Voice Synthesis 40 Conclusion 47 Acknowledgments Author: Britt Paris, assistant professor of Library and Information Science, Rutgers University; PhD, 2018,Information Studies, University of California, Los Angeles. Author: Joan Donovan, director of the Technology and Social Change Research Project, Harvard Kennedy School; PhD, 2015, Sociology and Science Studies, University of California San Diego. This report is published under Data & Society’s Media Manipulation research initiative; for more information on the initiative, including focus areas, researchers, and funders, please visit https://datasociety.net/research/ media-manipulation DATA & SOCIETY - 2 - EXECUTIVE SUMMARY Do deepfakes signal an information apocalypse? Are they the end of evidence as we know it? The answers to these questions require us to understand what is truly new about contemporary AV manipulation and what is simply an old struggle for power in a new guise. The first widely-known examples of amateur, AI-manipulated, face swap videos appeared in November 2017. Since then, the news media, and therefore the general public, have begun to use the term “deepfakes” to refer to this larger genre of videos—videos that use some form of deep or machine learning to hybridize or generate human bodies and faces. -
Digital Platform As a Double-Edged Sword: How to Interpret Cultural Flows in the Platform Era
International Journal of Communication 11(2017), 3880–3898 1932–8036/20170005 Digital Platform as a Double-Edged Sword: How to Interpret Cultural Flows in the Platform Era DAL YONG JIN Simon Fraser University, Canada This article critically examines the main characteristics of cultural flows in the era of digital platforms. By focusing on the increasing role of digital platforms during the Korean Wave (referring to the rapid growth of local popular culture and its global penetration starting in the late 1990s), it first analyzes whether digital platforms as new outlets for popular culture have changed traditional notions of cultural flows—the forms of the export and import of popular culture mainly from Western countries to non-Western countries. Second, it maps out whether platform-driven cultural flows have resolved existing global imbalances in cultural flows. Third, it analyzes whether digital platforms themselves have intensified disparities between Western and non- Western countries. In other words, it interprets whether digital platforms have deepened asymmetrical power relations between a few Western countries (in particular, the United States) and non-Western countries. Keywords: digital platforms, cultural flows, globalization, social media, asymmetrical power relations Cultural flows have been some of the most significant issues in globalization and media studies since the early 20th century. From television programs to films, and from popular music to video games, cultural flows as a form of the export and import of cultural materials have been increasing. Global fans of popular culture used to enjoy films, television programs, and music by either purchasing DVDs and CDs or watching them on traditional media, including television and on the big screen. -
Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook
University of Pennsylvania ScholarlyCommons Marketing Papers Wharton Faculty Research 1-2018 Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook Dokyun Lee Kartik Hosanagar University of Pennsylvania Harikesh Nair Follow this and additional works at: https://repository.upenn.edu/marketing_papers Part of the Advertising and Promotion Management Commons, Business Administration, Management, and Operations Commons, Business Analytics Commons, Business and Corporate Communications Commons, Communication Technology and New Media Commons, Marketing Commons, Mass Communication Commons, Social Media Commons, and the Technology and Innovation Commons Recommended Citation Lee, D., Hosanagar, K., & Nair, H. (2018). Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook. Management Science, http://dx.doi.org/10.1287/mnsc.2017.2902 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/marketing_papers/339 For more information, please contact [email protected]. Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook Abstract We describe the effect of social media advertising content on customer engagement using data from Facebook. We content-code 106,316 Facebook messages across 782 companies, using a combination of Amazon Mechanical Turk and natural language processing algorithms. We use this data set to study the association of various kinds of social media marketing content with user engagement—defined as Likes, comments, shares, and click-throughs—with the messages. We find that inclusion of widely used content related to brand personality—like humor and emotion—is associated with higher levels of consumer engagement (Likes, comments, shares) with a message. We find that directly informative content—like mentions of price and deals—is associated with lower levels of engagement when included in messages in isolation, but higher engagement levels when provided in combination with brand personality–related attributes. -
Deepfakes and Cheap Fakes
DEEPFAKES AND CHEAP FAKES THE MANIPULATION OF AUDIO AND VISUAL EVIDENCE Britt Paris Joan Donovan DEEPFAKES AND CHEAP FAKES - 1 - CONTENTS 02 Executive Summary 05 Introduction 10 Cheap Fakes/Deepfakes: A Spectrum 17 The Politics of Evidence 23 Cheap Fakes on Social Media 25 Photoshopping 27 Lookalikes 28 Recontextualizing 30 Speeding and Slowing 33 Deepfakes Present and Future 35 Virtual Performances 35 Face Swapping 38 Lip-synching and Voice Synthesis 40 Conclusion 47 Acknowledgments Author: Britt Paris, assistant professor of Library and Information Science, Rutgers University; PhD, 2018,Information Studies, University of California, Los Angeles. Author: Joan Donovan, director of the Technology and Social Change Research Project, Harvard Kennedy School; PhD, 2015, Sociology and Science Studies, University of California San Diego. This report is published under Data & Society’s Media Manipulation research initiative; for more information on the initiative, including focus areas, researchers, and funders, please visit https://datasociety.net/research/ media-manipulation DATA & SOCIETY - 2 - EXECUTIVE SUMMARY Do deepfakes signal an information apocalypse? Are they the end of evidence as we know it? The answers to these questions require us to understand what is truly new about contemporary AV manipulation and what is simply an old struggle for power in a new guise. The first widely-known examples of amateur, AI-manipulated, face swap videos appeared in November 2017. Since then, the news media, and therefore the general public, have begun to use the term “deepfakes” to refer to this larger genre of videos—videos that use some form of deep or machine learning to hybridize or generate human bodies and faces. -
Content Social Media
content & social media CONTENT & SOCIAL MEDIA / 1 Introduction A couple of years ago, people were more insistent on keeping content marketing and social media marketing divided as clearly separate entities. However, as social media platforms have evolved and the ways in which brands communicate have changed to reflect such changes, the concepts of content vs social have started to blur. Ultimately, it doesn’t really matter if you’re writing a blog or you’re writing a social media post - both are content and both have the potential of helping you generate traffic, leads and sales. In the realm of social media, content is simply approached in a different way. You’re not writing an 800-word blog (at least not typically), rather you’re publishing shorter, easier- to-digest posts. Some may be text, others may be photos or videos, some may be a combination of these types. Depending on the platform, the kind of content you can craft also changes drastically. A simple example is Twitter’s restrictive 140-character limit per tweet - a parameter that essentially makes it a social microblog. CONTENT & SOCIAL MEDIA / 2 In this eBook, we will be looking at some of the most important points to remember when it comes to creating content on social media. These include: • IDENTIFYING AND UNDERSTANDING THE QUIRKS OF DIFFERENT SOCIAL MEDIA PLATFORMS - Facebook - Twitter - LinkedIn - Instagram - Google+ • CONSIDERING YOUR CONTENT - Text posts - Media / Photos & Videos - External links • THE IMPORTANCE OF CONSISTENCY CONTENT & SOCIAL MEDIA / 3 understanding thE Quirks of your social media platform Here’s a list of just some of the SOCIAL MEDIA PLATFORMS out there: Facebook Tumblr Twitter Snapchat LinkedIn Pinterest Instagram Myspace (yes, it still exists) Vine YouTube Google+ And potentially hundreds of other, smaller and lesser-known social networks The number is overwhelming, but the good news is that you can cut this list down to some of its key players. -
Facebook Timeline
Facebook Timeline 2003 October • Mark Zuckerberg releases Facemash, the predecessor to Facebook. It was described as a Harvard University version of Hot or Not. 2004 January • Zuckerberg begins writing Facebook. • Zuckerberg registers thefacebook.com domain. February • Zuckerberg launches Facebook on February 4. 650 Harvard students joined thefacebook.com in the first week of launch. March • Facebook expands to MIT, Boston University, Boston College, Northeastern University, Stanford University, Dartmouth College, Columbia University, and Yale University. April • Zuckerberg, Dustin Moskovitz, and Eduardo Saverin form Thefacebook.com LLC, a partnership. June • Facebook receives its first investment from PayPal co-founder Peter Thiel for US$500,000. • Facebook incorporates into a new company, and Napster co-founder Sean Parker becomes its president. • Facebook moves its base of operations to Palo Alto, California. N. Lee, Facebook Nation, DOI: 10.1007/978-1-4614-5308-6, 211 Ó Springer Science+Business Media New York 2013 212 Facebook Timeline August • To compete with growing campus-only service i2hub, Zuckerberg launches Wirehog. It is a precursor to Facebook Platform applications. September • ConnectU files a lawsuit against Zuckerberg and other Facebook founders, resulting in a $65 million settlement. October • Maurice Werdegar of WTI Partner provides Facebook a $300,000 three-year credit line. December • Facebook achieves its one millionth registered user. 2005 February • Maurice Werdegar of WTI Partner provides Facebook a second $300,000 credit line and a $25,000 equity investment. April • Venture capital firm Accel Partners invests $12.7 million into Facebook. Accel’s partner and President Jim Breyer also puts up $1 million of his own money. -
Estimating Age and Gender in Instagram Using Face Recognition: Advantages, Bias and Issues. / Diego Couto De Las Casas
ESTIMATING AGE AND GENDER IN INSTAGRAM USING FACE RECOGNITION: ADVANTAGES, BIAS AND ISSUES. DIEGO COUTO DE. LAS CASAS ESTIMATING AGE AND GENDER IN INSTAGRAM USING FACE RECOGNITION: ADVANTAGES, BIAS AND ISSUES. Dissertação apresentada ao Programa de Pós-Graduação em Ciência da Computação do Instituto de Ciências Exatas da Univer- sidade Federal de Minas Gerais – Depar- tamento de Ciência da Computação como requisito parcial para a obtenção do grau de Mestre em Ciência da Computação. Orientador: Virgílio Augusto Fernandes de Almeida Belo Horizonte Fevereiro de 2016 DIEGO COUTO DE. LAS CASAS ESTIMATING AGE AND GENDER IN INSTAGRAM USING FACE RECOGNITION: ADVANTAGES, BIAS AND ISSUES. Dissertation presented to the Graduate Program in Ciência da Computação of the Universidade Federal de Minas Gerais – De- partamento de Ciência da Computação in partial fulfillment of the requirements for the degree of Master in Ciência da Com- putação. Advisor: Virgílio Augusto Fernandes de Almeida Belo Horizonte February 2016 © 2016, Diego Couto de Las Casas. Todos os direitos reservados Ficha catalográfica elaborada pela Biblioteca do ICEx - UFMG Las Casas, Diego Couto de. L337e Estimating age and gender in Instagram using face recognition: advantages, bias and issues. / Diego Couto de Las Casas. – Belo Horizonte, 2016. xx, 80 f. : il.; 29 cm. Dissertação (mestrado) - Universidade Federal de Minas Gerais – Departamento de Ciência da Computação. Orientador: Virgílio Augusto Fernandes de Almeida. 1. Computação - Teses. 2. Redes sociais on-line. 3. Computação social. 4. Instagram. I. Orientador. II. Título. CDU 519.6*04(043) Acknowledgments Gostaria de agradecer a todos que me fizeram chegar até aqui. Àminhafamília,pelosconselhos,pitacoseportodoosuporteaolongodesses anos. Aos meus colegas do CAMPS(-Élysées),pelascolaborações,pelasrisadasepelo companheirismo. -
Artificial Intelligence: Risks to Privacy and Democracy
Artificial Intelligence: Risks to Privacy and Democracy Karl Manheim* and Lyric Kaplan** 21 Yale J.L. & Tech. 106 (2019) A “Democracy Index” is published annually by the Economist. For 2017, it reported that half of the world’s countries scored lower than the previous year. This included the United States, which was de- moted from “full democracy” to “flawed democracy.” The princi- pal factor was “erosion of confidence in government and public in- stitutions.” Interference by Russia and voter manipulation by Cam- bridge Analytica in the 2016 presidential election played a large part in that public disaffection. Threats of these kinds will continue, fueled by growing deployment of artificial intelligence (AI) tools to manipulate the preconditions and levers of democracy. Equally destructive is AI’s threat to deci- sional and informational privacy. AI is the engine behind Big Data Analytics and the Internet of Things. While conferring some con- sumer benefit, their principal function at present is to capture per- sonal information, create detailed behavioral profiles and sell us goods and agendas. Privacy, anonymity and autonomy are the main casualties of AI’s ability to manipulate choices in economic and po- litical decisions. The way forward requires greater attention to these risks at the na- tional level, and attendant regulation. In its absence, technology gi- ants, all of whom are heavily investing in and profiting from AI, will dominate not only the public discourse, but also the future of our core values and democratic institutions. * Professor of Law, Loyola Law School, Los Angeles. This article was inspired by a lecture given in April 2018 at Kansai University, Osaka, Japan. -
View Was Conducted with a Convenience Sample of Patients Being Treated for MM
JMIR Cancer Patient-Centered Innovations, Education and Technology for Cancer Care and Cancer Research Volume 4 (2018), Issue 2 ISSN: 2369-1999 Contents Original Papers Barriers and Facilitators of Using Sensored Medication Adherence Devices in a Diverse Sample of Patients With Multiple Myeloma: Qualitative Study (e12) Alemseged Asfaw, Connie Yan, Karen Sweiss, Scott Wirth, Victor Ramirez, Pritesh Patel, Lisa Sharp. 3 Web-Based Patient-Reported Outcomes Using the International Consortium for Health Outcome Measurement Dataset in a Major German University Hospital: Observational Study (e11373) Maria Karsten, Dorothee Speiser, Claudia Hartmann, Nele Zeuschner, Kai Lippold, Verena Kiver, Peter Gocke, Valerie Kirchberger, Jens-Uwe Blohmer. 14 Online Decision Support Tool for Personalized Cancer Symptom Checking in the Community (REACT): Acceptability, Feasibility, and Usability Study (e10073) Marzena Nieroda, Artitaya Lophatananon, Brian McMillan, Li-Chia Chen, John Hughes, Rona Daniels, James Clark, Simon Rogers, Kenneth Muir. 22 Association Between Adherence to Cancer Screening and Knowledge of Screening Guidelines: Feasibility Study Linking Self-Reported Survey Data With Medical Records (e10529) Aisha Lofters, Deanna Telner, Sumeet Kalia, Morgan Slater. 38 Exploring the Most Visible German Websites on Melanoma Immunotherapy: A Web-Based Analysis (e10676) Julia Brütting, Theresa Steeb, Lydia Reinhardt, Carola Berking, Friedegund Meier. 51 Reliability of Cancer Treatment Information on the Internet: Observational Study (e10031) Ryo Ogasawara, Noriyuki Katsumata, Tatsushi Toyooka, Yuko Akaishi, Takaaki Yokoyama, Gemmu Kadokura. 61 How to Optimize Health Messages About Cancer on Facebook: Mixed-Methods Study (e11073) Priscila Biancovilli, Claudia Jurberg. 68 A Rapid Process for Identifying and Prioritizing Technology-Based Tools for Health System Implementation (e11195) Emily Dibble, Bradley Iott, Allen Flynn, Darren King, Mark MacEachern, Charles Friedman, Tanner Caverly. -
The Silencing Power of Algorithms: How the Facebook News Feed Algorithm Manipulates Users’ Perceptions of Opinion Climates
Portland State University PDXScholar University Honors Theses University Honors College March 2019 The Silencing Power of Algorithms: How the Facebook News Feed Algorithm Manipulates Users’ Perceptions of Opinion Climates Callie Jessica Morgan Portland State University Follow this and additional works at: https://pdxscholar.library.pdx.edu/honorstheses Let us know how access to this document benefits ou.y Recommended Citation Morgan, Callie Jessica, "The Silencing Power of Algorithms: How the Facebook News Feed Algorithm Manipulates Users’ Perceptions of Opinion Climates" (2019). University Honors Theses. Paper 661. This Thesis is brought to you for free and open access. It has been accepted for inclusion in University Honors Theses by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. Running head: SILENCING POWER OF ALGORITHMS 1 The Silencing Power of Algorithms: How the Facebook News Feed Algorithm Manipulates Users’ Perceptions of Opinion Climates Callie Morgan University Honors College Portland State University Advisor: Dr. Erin Spottswood SILENCING POWER OF ALGORITHMS 2 Abstract This extended literature review investigates how the architecture and features of the Facebook Newsfeed algorithm, EdgeRank, can inhibit and facilitate the expression of political opinions. This paper will investigate how Elisabeth Noelle-Neumann’s theory on public opinion, Spiral of Silence, can be used to assess the Facebook news feed as a political opinion source that actively shapes users’ perceptions of minority and majority opinion climates. The feedback loops created by the algorithm’s criteria influences users’ decisions to self-censor or express their political opinions with interpersonal connections and unfamiliar connections on the site. -
CS 182: Ethics, Public Policy, and Technological Change
Rob Reich CS 182: Ethics, Public Policy, and Mehran Sahami Jeremy Weinstein Technological Change Hilary Cohen Housekeeping • Recording of information session on Public Policy memo available on class website • Also posted on the website is a recent research study on the efficacy of contact tracing apps (if you’re interested) Today’s Agenda 1. Perspectives on data privacy 2. Approaches to data privacy • Anonymization • Encryption • Differential Privacy 3. What can we infer from your digital trails? 4. The information ecosystem 5. Facial recognition Today’s Agenda 1. Perspectives on data privacy 2. Approaches to data privacy • Anonymization • Encryption • Differential Privacy 3. What can we infer from your digital trails? 4. The information ecosystem 5. Facial recognition Perspectives on Data Privacy • Data privacy often involves a balance of competing interests • Making data available for meaningful analysis • For public goods • Auditing algorithmic decision-making for fairness • Medical research and health care improvement • Protecting national security • For private goods • Personalized advertising • Protecting individual privacy • Personal value of privacy and respect for individual – thanks Rob! • Freedom of speech and activity • Avoiding discrimination • Regulation: FERPA, HIPAA, GDPR, etc. – thanks Jeremy! • Preventing access from “adversaries” Today’s Agenda 1. Perspectives on data privacy 2. Approaches to data privacy • Anonymization • Encryption • Differential Privacy 3. What can we infer from your digital trails? 4. The information ecosystem 5. Facial recognition Anonymization • Basic idea: drop personally identifying features from the data Name SS# Employer Job Title Nationality Gender D.O.B Zipcode Has Condition? Mehran XXX-XX- Stanford Professor Iran Male May 10, 94306 No Sahami XXXX University 1970 Claire XXX-XX- Google Inc. -
Predicting User Interaction on Social Media Using Machine Learning Chad Crowe University of Nebraska at Omaha
University of Nebraska at Omaha DigitalCommons@UNO Student Work 11-2018 Predicting User Interaction on Social Media using Machine Learning Chad Crowe University of Nebraska at Omaha Follow this and additional works at: https://digitalcommons.unomaha.edu/studentwork Part of the Computer Sciences Commons Recommended Citation Crowe, Chad, "Predicting User Interaction on Social Media using Machine Learning" (2018). Student Work. 2920. https://digitalcommons.unomaha.edu/studentwork/2920 This Thesis is brought to you for free and open access by DigitalCommons@UNO. It has been accepted for inclusion in Student Work by an authorized administrator of DigitalCommons@UNO. For more information, please contact [email protected]. Predicting User Interaction on Social Media using Machine Learning A Thesis Presented to the College of Information Science and Technology and the Faculty of the Graduate College University of Nebraska at Omaha In Partial Fulfillment of the Requirements for the Degree Master of Science in Computer Science by Chad Crowe November 2018 Supervisory Committee Dr. Brian Ricks Dr. Margeret Hall Dr. Yuliya Lierler ProQuest Number:10974767 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. ProQuest 10974767 Published by ProQuest LLC ( 2019). Copyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code Microform Edition © ProQuest LLC.