#Resistance: A Final Project Statement

The #Resistance final project documents the “rogue” government Twitter Resistance movement that to respond to the Trump administration’s social media gag order on federal agencies. Using Documenting the Now’s twarc tool, this project reviews the activity of nine accounts in regards to their conversations, engagement, and language in parodying a government agency. Talking about everything from climate change to internal affairs of the White House, these accounts have played an important role in the coverage of the first 100 days of the Trump administration. This project seeks to document aspects of this coverage by exploring how #Resistance defines itself on Twitter.

What can we learn from “rogue” Twitter about digital activism? What can this movement teach us about advocacy and government in digital public spaces? And where do these two ideas fit into the larger aims of Twitter culture – as noise, or as something greater?

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Calling Something a Dataset: Visualizing the Crystal Palace

Since December, I’ve been working with Steven Lubar for a presentation at Bard College last week. The event focused on the 1853 New York Crystal Palace. Lubar has introduced his presentation over at Medium. (Parts one through three are up at the moment – the next installment will complement this piece.)

Most of my time with this project has been cleaning, wrangling, and interrogating the dataset. (Side note: does anyone remember that poem about literary analysis being like torture? It sometimes feels that way with datasets too.) As we’ve discussed in class, cleaning data is a never-ending process – the data we started with wasn’t raw, but carefully curated OCR from a Cornell Library database. In wrangling the data into a CSV and under headings specific to our needs, we shifted the catalog as a book into a catalog as a database, bringing up multiple questions of historical and technical interest.

Working through the data as a whole and as individual objects, Lubar and I worked to figure out what kind of questions could be explored in the catalog. What was this exhibition? What was interesting about it? What kind of information was collected for the catalog?

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It’s Britney, Bitch: Commentary on Distortion in Spears’s Use of Social Media

THE IDEA

As someone who at times seems to only exist on Twitter, I’m fascinated by the ways in which people use the platform to craft their own narratives. But I also love the off-the-beaten-path accounts – bots, parodies, and what I like to call commentary.

I spend a lot of time looking at this third type, namely through examples of @WillMcAvoyACN and @SwiftOnSecurity. I stand by my point that these are not parody accounts. In the latter, as much as they’re prenteding to be Taylor Swift, they’re not going through the daily motions or documenting on her activities. Instead, it’s almost like she was dropped in an alternative dimension – same music, same image, but just talking about tech security instead of herself. Taylor’s persona, which was much more present at the beginning of the account than it is now, served as a gimmick to interest people in the content. McAvoy is a bit different – it’s a fictional persona – but it still prioritizes content over defined character. In his interactions with fans as well as real-life reporters, McAvoy serves as a commentary of journalism by playing through the persona as well as commenting on its usage to hold people accountable for the things they say.

So, as I wrote on Slack:

Inspired by the Twitter account SwiftOnSecurity, I’m looking to build a Twitter profile that engages/raises awareness around a keyword, but doing so through a persona that challenges or distorts the messages being presented. How does this observational view of a topic – one that a persona may have a reasonable stake in – change the ways in which we understand the topic? And in what ways do the tools available on Twitter – GIFs, photos, hashtags, polls, locations – distort or shape the ways in which we understand the project? Thinking around questions from Chun and Parise, why do we invest in this information even when the likelihood of the person behind it false? In what ways does this allow us to imagine the persona and the issues complexly? Can we explore these complexities in a project like this? In what ways do we see a persona like SwiftOnSecurity highlighting or hiding the relationship? Ideally, I’ll be looking at both my construction and reception by an audience (depending on what kind of audience is generated) to talk about how distortion functions in this environment.

 

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