A book at the intersection of data science and media studies, presenting concepts and methods for computational analysis of cultural data. How can we see a billion images? What analytical methods can we bring to bear on the astonishing scale of digital culture--the billions of photographs shared on social media every day, the hundreds of millions of songs created by twenty million musicians on Soundcloud, the content of four billion Pinterest boards? In Cultural Analytics, Lev Manovich presents concepts and methods for computational analysis of cultural data. Drawing on more than a decade of research and projects from his own lab, Manovich offers a gentle, nontechnical introduction to the core ideas of data analytics and discusses the ways that our society uses data and algorithms.

A book at the intersection of data science and media studies, presenting concepts and methods for computational analysis of cultural data. How can we see a billion images? What analytical methods can we bring to bear on the astonishing scale of digital culture--the billions of photographs shared on social media every day, the hundreds of millions of songs created by twenty million musicians on Soundcloud, the content of four billion Pinterest boards? In Cultural Analytics, Lev Manovich presents concepts and methods for computational analysis of cultural data. Drawing on more than a decade of research and projects from his own lab, Manovich offers a gentle, nontechnical introduction to the core ideas of data analytics and discusses the ways that our society uses data and algorithms.

How can I take a data-driven approach to company culture? What should I measure and which metrics should I focus on? How can I use people analytics and behavioural science impact culture? Based on insights from the largest ever behavioural research study which examined the organizational impact of 220+ behaviours from 60 organizations, across 61 countries, Culture Analytics provides an evidence-based approach to organizational culture. It outlines the leading and lagging culture indicators, explains how to identify actionable insights from your people and culture data as well as how to apply predictive analytics to company culture. There is also guidance on the 30 employee behaviours which have the most impact on company culture and how to apply behavioural science interventions to drive these in your organization. The second part of the book covers key areas where culture analytics can be applied to drive business performance. These areas include talent acquisition and retention, employee engagement, EDI (equity, diversity and inclusion), wellbeing, psychological safety as well as resilience, strategy, innovation, change management and risk. Full of practical advice, this book also includes real world examples from Barclays, Pfizer, American Airlines, EDF Energy, Saudi Telecom Company, Cisco and Ethiad Airways. Making the complex world of people analytics and behavioural science accessible and applicable to all senior HR professionals and business leaders, Culture Analytics shows how to take a robust, evidence-based approach to company culture to drive workforce and organizational performance and deliver tangible business value.

The digital revolution fundamentally changed how cultural heritage is created, documented, analyzed, and preserved. The book focuses on this transformation’s impact. How must museums and archives meet the challenges of digitally generated cultures and how does the digital revolution influence traditional object collection, research, and education? How do digital technologies and digital art and culture affect our interaction with images? Leading international experts from various disciplines break new ground. Pioneering interdisciplinary research results collected in this book are relevant to education, curators and archivists in the arts and culture sector and in the digital humanities.

This book considers the challenges related to the effective implementation of artificial intelligence (AI) and machine learning (ML) technologies to the cultural heritage digitization process. Particular focus is placed on improvements to the data acquisition stage, as well as the data enrichment and curation stages, using advanced artificial intelligence techniques and tools. An emphasis is placed on recent applications related to deep learning for visual recognition, generative models, natural language processing, and super resolution. The book is a valuable reference for researchers working in the multidisciplinary field of cultural heritage and AI, as well as professional experts in the art and culture domains, such as museums, libraries, and historic sites and buildings. Reports on techniques and methods that leverage AI and machine learning and their impact on the digitization of cultural heritage; Addresses challenges of improving data acquisition, enrichment and management processes; Highlights contributions from international researchers from diverse fields and subject areas.

An international business expert helps you understand and navigate cultural differences in this insightful and practical guide, perfect for both your work and personal life. Americans precede anything negative with three nice comments; French, Dutch, Israelis, and Germans get straight to the point; Latin Americans and Asians are steeped in hierarchy; Scandinavians think the best boss is just one of the crowd. It's no surprise that when they try and talk to each other, chaos breaks out. In The Culture Map, INSEAD professor Erin Meyer is your guide through this subtle, sometimes treacherous terrain in which people from starkly different backgrounds are expected to work harmoniously together. She provides a field-tested model for decoding how cultural differences impact international business, and combines a smart analytical framework with practical, actionable advice.

The canon of postwar American fiction has changed over the past few decades to include far more writers of color. It would appear that we are making progress—recovering marginalized voices and including those who were for far too long ignored. However, is this celebratory narrative borne out in the data? Richard Jean So draws on big data, literary history, and close readings to offer an unprecedented analysis of racial inequality in American publishing that reveals the persistence of an extreme bias toward white authors. In fact, a defining feature of the publishing industry is its vast whiteness, which has denied nonwhite authors, especially black writers, the coveted resources of publishing, reviews, prizes, and sales, with profound effects on the language, form, and content of the postwar novel. Rather than seeing the postwar period as the era of multiculturalism, So argues that we should understand it as the invention of a new form of racial inequality—one that continues to shape the arts and literature today. Interweaving data analysis of large-scale patterns with a consideration of Toni Morrison’s career as an editor at Random House and readings of individual works by Octavia Butler, Henry Dumas, Amy Tan, and others, So develops a form of criticism that brings together qualitative and quantitative approaches to the study of literature. A vital and provocative work for American literary studies, critical race studies, and the digital humanities, Redlining Culture shows the importance of data and computational methods for understanding and challenging racial inequality.