Data Versus Democracy: How Big Data Algorithms Shape Opinions and Alter the Course of History (Paperback)

Shaffer, Kris

商品描述

Human attention is in the highest demand it has ever been. The drastic increase in available information has compelled individuals to find a way to sift through the media that is literally at their fingertips. Content recommendation systems have emerged as the technological solution to this social and informational problem, but they've also created a bigger crisis in confirming our biases by showing us only, and exactly, what it predicts we want to see. Data versus Democracy investigates and explores how, in the era of social media, human cognition, algorithmic recommendation systems, and human psychology are all working together to reinforce (and exaggerate) human bias. The dangerous confluence of these factors is driving media narratives, influencing opinions, and possibly changing election results.
In this book, algorithmic recommendations, clickbait, familiarity bias, propaganda, and other pivotal concepts are analyzed and then expanded upon via fascinating and timely case studies: the 2016 US presidential election, Ferguson, GamerGate, international political movements, and more events that come to affect every one of us. What are the implications of how we engage with information in the digital age? Data versus Democracy explores this topic and an abundance of related crucial questions. We live in a culture vastly different from any that has come before. In a society where engagement is currency, we are the product. Understanding the value of our attention, how organizations operate based on this concept, and how engagement can be used against our best interests is essential in responsibly equipping ourselves against the perils of disinformation.


Who This Book Is For
Individuals who are curious about how social media algorithms work and how they can be manipulated to influence culture. Social media managers, data scientists, data administrators, and educators will find this book particularly relevant to their work.

 

商品描述(中文翻譯)

人類的注意力需求是有史以來最高的。大量的資訊供應使個人不得不找到一種方法來篩選他們指尖上的媒體。內容推薦系統已經成為解決這個社會和資訊問題的技術解決方案,但它們也創造了一個更大的危機,即通過只顯示和確切預測我們想看到的內容來確認我們的偏見。《數據對抗民主》探討和研究了在社交媒體時代,人類認知、算法推薦系統和人類心理如何共同加強(和誇大)人類偏見。這些因素的危險交匯正在推動媒體敘事,影響觀點,並可能改變選舉結果。

在這本書中,算法推薦、點擊誘餌、熟悉性偏見、宣傳和其他關鍵概念通過引人入勝且及時的案例研究進行了分析和拓展:2016年美國總統選舉、弗格森事件、GamerGate、國際政治運動等等影響我們每個人的事件。在數字時代,我們如何與信息互動的影響是什麼?《數據對抗民主》探討了這個主題以及許多相關的重要問題。我們生活在一個與以往任何時候都不同的文化中。在一個以參與度為貨幣的社會中,我們就是產品。了解我們的注意力價值,組織如何基於這一概念運作,以及如何利用參與度來反對我們的最佳利益,對於負責任地應對虛假信息的危險至關重要。

這本書適合對社交媒體算法運作方式和如何操縱其影響文化感興趣的個人。社交媒體經理、數據科學家、數據管理員和教育工作者將會發現這本書對他們的工作特別相關。

作者簡介

Kris Shaffer, Ph.D., is a data scientist and Senior Computational Disinformation Analyst for New Knowledge. He co-authored "The Tactics and Tropes of the Internet Research Agency," a report prepared for the United States Senate Select Committee on Intelligence about Russian interference in the 2016 US presidential election on social media. He has consulted for multiple US government agencies, non-profits, and universities on matters related to digital disinformation, data ethics, and digital pedagogy.
In a former (professional) life, Kris was an academic and digital humanist. He has taught courses in music theory and cognition, computer science, and digital studies at Yale University, University of Colorado-Boulder, University of Mary Washington, and Charleston Southern University. He holds a PhD from Yale University.

作者簡介(中文翻譯)

Kris Shaffer博士是一位資料科學家,也是New Knowledge的高級計算假訊息分析師。他共同撰寫了一份報告,名為「The Tactics and Tropes of the Internet Research Agency」,該報告是為美國參議院情報委員會準備的,關於俄羅斯在社交媒體上干預2016年美國總統選舉的行為。他曾為多個美國政府機構、非營利組織和大學提供諮詢服務,內容涉及數字假訊息、數據倫理和數字教學等問題。

在之前的(專業)生涯中,Kris是一位學者和數字人文學家。他曾在耶魯大學、科羅拉多大學波德分校、瑪麗華盛頓大學和查爾斯頓南方大學教授音樂理論和認知、計算機科學和數字研究等課程。他擁有耶魯大學的博士學位。