Mining the Media Archive gathers together an exciting collection of essays by writer and cultural theorist Dot Tuer. Ranging from monographs on new media artists to a history of Canada's most controversial artist-run centre, the CEAC, to testimonial writing on cultural politics and post-colonialism in Canada and Argentina, Tuer's writings address issues of global media and local remembrance through a unique blend of storytelling, archival research and cultural analysis.

BuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language. Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: Write Python scripts and use APIs to gather data from the social web Download data archives and dig through them for insights Inspect HTML downloaded from websites for useful content Format, aggregate, sort, and filter your collected data using Google Sheets Create data visualizations to illustrate your discoveries Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library Apply what you've learned to research topics on your own Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.

BuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language. Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: Write Python scripts and use APIs to gather data from the social web Download data archives and dig through them for insights Inspect HTML downloaded from websites for useful content Format, aggregate, sort, and filter your collected data using Google Sheets Create data visualizations to illustrate your discoveries Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library Apply what you've learned to research topics on your own Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.

How do we rely on media for remembering? In exploring the complex ways that media converge to support our desire to capture, store and retrieve memories, this textbook offers analyses of representations of memorable events, media tools for remembering and forgetting, media technologies for archiving and the role of media producers in making memories. Theories of memory and media are covered alongside an accessible range of case studies focusing on memory in relation to radio, television, pop music, celebrity, digital media and mobile phones. Ethnographic and production culture research, including interviews with members of the public and industry professionals, is also included. Offering a comprehensive introduction to the connections and disconnections in the study of media and memory, this is the perfect textbook for media studies students.

Features essays that combine research, critical analyses and theoretical approaches regarding the meaning and value of amateur and archival films. This book identifies home movies as methods of visually preserving history. It defines a genre of film studies and establishes the home movie as a tool for extracting historical and social insights.

“A meticulous mixture of social and family history . . . Whether or not you have mining connections, this is an interesting socio-economic read.” —Your Family Tree In the 1920s there were over a million coalminers working in over 3000 collieries across Great Britain, and the industry was one of the most important and powerful in British history. It dominated the lives of generations of individuals, their families, and communities, and its legacy is still with us today—many of us have a coalmining ancestor. Yet family historians often have problems in researching their mining forebears. Locating the relevant records, finding the sites of the pits, and understanding the work involved and its historical background can be perplexing. That is why Brian Elliott’s concise, authoritative and practical handbook will be so useful, for it guides researchers through these obstacles and opens up the broad range of sources they can go to in order to get a vivid insight into the lives and experiences of coalminers in the past. His overview of the coalmining history—and the case studies and research tips he provides—will make his book rewarding reading for anyone looking for a general introduction to this major aspect of Britain’s industrial heritage. His directory of regional and national sources and his commentary on them will make this guide an essential tool for family historians searching for an ancestor who worked in coalmining underground, on the pit top or just lived in a mining community. As featured in Who Do You Think You Are? Magazine and the Barnsley Chronicle.

In this three-volume series, editor Jessica Wyman assembles essays that consider the developments and directions of the use of text in visual art, exploring what personal, social or political motivations inspire artists to use text and how text-based art is understood. Volume 1 examines the use of text in concept-based art.