COVID-19 and the Residue It Leaves Us as a Society

COVID-19, the disease that causes a respiratory illness with flu-like symptoms, has forever changed and reshaped the way the society has comfortably settled in for the past century of the industrial and information era.    Unless if one is in a remote part of the world untied to society, everyone has been affected by the political, economic, and social consequences.

Zoom - If it weren't popular already for companies using videoconferencing for telecommuting, the Zoom app has shot up to ubiquity for most who are now working from home, with one media outlet christening it as the "darling of remote workers."   It's quickly becoming a verb for those who need to community digitally over the web and sits atop as of the most popular free apps in dozens of countries.   It speaks the future of working for those who don't need an office or an organization that doesn't necessarily need to spare physical spaces for its workforce, particularly as workers become disposable upon projects.  It's an eerie

Amazon - "Coronavirus Is Speeding Up the Amazonification of the Planet" as one article puts it, and as restaurants, bars, and local shops close down, Amazon is quickly swooping to fill the void of customers and jobs.  Amazon is taking advantage of the gap by welcoming these unemployed staffers "until things return to normal and their past employer is able to bring them back" - which of course may take a while -- or never -- depending on the economic damage of Covid-19. The consumer shift to online retailers from physical storefronts has been happening already, and this may be the tipping point in accelerating the takeover over the retail market.   I can't blame Amazon.  I simply can purchase more items instantaneously with a click of a button and forget about it until it arrives at my front door.

Netflix - In this age of the pandemic, who isn't streaming from an online service during those quiet quarantine hours into the night?   It seems like what entertained you yesterday evening on Netflix has become watercooler talk.   Aside from its entertainment, Netflix has really driven home the ubiquity of streaming collections and digital platforms that consumers now rely on more so than ever along with broadband internet.  Of course, it's not just Netflix, but other services such as Amazon Prime, Hulu, HBO GO, and Xfinity.   While on the one hand this divergence away from the cable networks and big Hollywood may appear to disrupt traditional media platforms, has it really changed anything? It seems that much of the same monolithic and cultural hegemony continues albeit in another technology.    The question remains, what's really changed after this is all over?

Text Analysis: A Hermeneutical Exercise

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I'll be teaching a short intro workshop on text analysis using Voyant, an open-source, web-based application.   Geoffrey Rockwell (Professor of Philosophy and Humanities Computing at the University of Alberta, Canada) and Stéfan Sinclair (Associate Professor of Digital Humanities at McGill University) developed the application to support scholarly reading and interpretation of texts or corpus, particularly by scholars in the digital humanities.   I've been reading their text, Hermeneutica: Computer-Assisted Interpretation in the Humanities, to brush up on my knowledge in the teaching of the session to get to teach Using Voyant and the NLTK for Text Analysis.

 This video is part of the #dariahTeach platform (http://teach.dariah.eu), an open-source, community-driven platform for teaching and training materials for the digital arts and humanities.  As part of the course Introduction to Digital Humanities and the series Digital Humanities in Practice, this video discusses text visualization in Digital Humanities, emphasising that visualisation is not the end product but an intellectual process of thinking and interpreting text.

In their book in Hermeneutica, Rockwell and Sinclair suggest:

"In the slippage between our literary notion of a text and the computer's literal processing lie the disappointment and the possibility of text analysis.  Computers cannot understand a text for us.  They can, however, do things that may surprise us."  

Using Palladio and Gephi as Data Visualization Tools

Much has been published about data visualization tools.  Miriam Posner has written in this area which I often use as a reference.   Some have even commented on the variations and differences of Gephi and Palladio. 

Over the last year, I've been using Palladio to examine datasets of the Chinese headtax project, which makes it easy to create bivariate network graphs to illustrate relationships between two dimensions. By default, Palladio creates a force-directed layout, which is different from Gephi.   Palladio, at the same time, is only limited to this layout. The platform has no way of doing computational or algorithmic analysis of your graphs; you will need a more powerful program like Gephi to do that work.  The most powerful method for creating networks come from programming languages such as R, Python, and Javascript. These languages allow you to control various algorithmic and aesthetic aspects of network visualizations.  Any dimension of the data can be used as the source and target of a graph.

Regardless, I still find that knowing a bit of each of the data visualization tools would be helpful for any researcher, in any phase of their research process and lifecycle.   The following video tutorials is what helps me keep myself informed about not only how to use the tools, but also weighing the strengths and weaknesses of a particular approach to playing around with the data.  I'd be interested in hearing how you approach your data.  How do you learn the tools of your trade and then decide which would be the best for your own analyses? 

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