in progress.

The #MeToo movement, first trending in October 2017, is one of the latest social movements that has percolated into both virtual and physical spaces, prompting protests that have been widely covered over a variety of media sources. Historically, protest was relegated to highly-visible public spaces often directly facing a symbol of power, like the Capitol Building; but today, the virtual realm is fair game. How can activists maximize the power of virtual social movements? 


The data visualized above shows tweets from the month of October in 2017 that used the hashtag #MeToo. Each dot represents a twitter user—the online presence of an individual—and the size of the dot corresponds to the number of followers that account had at the time. The lines between dots represent common language between tweets; for instance, many people who used tagged their tweet with #MeToo also used #Resist or #TimesUp, referencing social movements that align with the Women’s Rights March, which occurred worldwide in January 2017. Exploring this data, interesting connections are drawn: Alyssa Milano, perhaps the most public-facing celebrity in the #MeToo movement, is represented by the largest dot, suggesting that the number of followers and the number of tweets she wrote on the subject have lots of influence for the movement. I used data from two primary sources: one dataset built by Ryan Deeds and shared online at, which simply scraped Twitter over a period of one month for tweets that used the #MeToo hashtag. The second source of data, also shared on, was produced by Brett Turner, which scraped Twitter over a two-month period, of which I only used one month to coincide with Deeds’ dataset. 


Case Study: How the #MeToo Movement Spread on Twitter
Conducted by Hugo Bowne-Anderson, a data journalist and member of the DataCamp online community, this research uses a variety of representational methods to explain the impact of the #MeToo movement on Twitter between October 24th and November 11th in 2017, around the first spark of this movement. I found this example while browsing for precedents for my own project, which also analyzes the #MeToo movement via virtual sources, but I was particularly struck by Bowne-Anderson’s use of diverse means of representation of this data, ranging from word clouds differing from week to week, to timelines of the hashtag’s use, to original tweets versus retweets, to the top five most popular tweets, and much more. Through this exhaustive spread of analysis, I think Bowne-Anderson paints a comprehensive picture of the movement and really emphasizes the extensive impact that virtual protest can have. Bowne-Anderson used the Twitter API to pull, according to him, “half a million recent tweets” that used the #MeToo hashtag. Surprisingly, this is the only method of data collection mentioned throughout this article, which proves that this dataset was clearly extremely fruitful for analysis. I don’t have much critique for this research; in fact, I am very impressed overall, particularly with the analysis of non-English language tweets and the impact of the movement in other countries outside the United States: especially with text-based data, this is an important distinction to make, as global and national impact may differ widely and lead to interesting findings. 

Case Study: How the Suburbs Will Swing the Midterm Election
Conducted by David Montgomery and Richard Florida for CityLab, this article utilizes a CityLab analysis “that classifies all 435 U.S. House districts according to their densities” into variations on rural, suburban, and urban typologies based on geography, politics, and population density. I chose this example because I read CityLab articles on a regular basis and this particular article struck me as incredibly relevant this moment in politics and seemed to be backed up with lots of interesting, manipulated data. By this, I mean that the data that was gathered is widely available, but was manipulated into categories (pure rural, rural-suburban mix, sparse suburban, dense suburban. And pure urban) in order to contribute to the narrative. The dataset used primarily in this study was produced by CityLab and is sourced by publicly-available information on vacant congressional seats, demographic data, election/political affiliation data, and more. In the end, the article attempts to unite the data of population and political density; however, I’m not so sure that this article is really as successful at telling a story as it could be. My primary critique is the authors’ lack of clarity: the data seems to have a lot of potential to say something about gerrymandering, or suburban voters who voted for Trump despite his policies that actively harm them, etc.; yet the conclusion of the article doesn’t say much more than “these things are related.” 

Case Study: We Feel Fine 
Conducted by data scientist Jonathan Harris, this beautiful visualization is constructed using a dataset comprised of data scraped from blogs all over the world that use the phrase “I feel” or “I am feeling.” The system records the sentence with this phrase and determines the general emotion expressed, happy, sad, angry, etc., and assigns a color to the data entry. Other information about that entry is saved, including local weather at the time of the blog post, location of blogger, time of day of blog post, and more, allowing readers to explore different facets that may have had emotional consequences. Besides being a visually pleasing experience, the project interestingly unites a highly-specific digital format with a vague, inherently-human way of experiencing the world. This project was perhaps most influential for me throughout this project.


In an age where accountability and political decentralization have risen to the forefront of national conversations regarding the agency of minorities, it is revealed that both physical and virtual realms are highly contested spaces to be mechanized for political gain. The market and state constantly vie for dominion over these spaces, whether falsely public parks or the Twittersphere; but these spaces must be claimed by and for collective citizens. Protests in the physical sphere are a historical tactic to bring awareness to an idea and influence the opinion of powerful entities like the market and state. But as the virtual realm has emerged as a similarly appropriate venue for dissent, citizen activists must learn to effectively appropriate and utilize this space to advocate for contested rights. 

Learning from a long history of physical protests, activists must learn to make virtual demonstrations highly visible, disruptive of routine, adaptive to changing contexts, and clear in intent. In physical spaces, it is often difficult to accommodate this requirement of spontaneity, with large masses of physical bodies unable to adapt quickly. In virtual space, the primary deterrent is clarity and surveillance: Twitter and other social media platforms, though often masquerading as public forums, are actually corporate entities that actively censor and disseminate messages via algorithms designed to amplify only those with the most followers. 

That’s where I began to be interested in this idea of influence and how that is tied up with follower counts. Largely stemming from celebrity Alyssa Milano’s Twitter-based accusations of sexual assault, the #MeToo movement was intended to spread awareness of the prevalence of sexual harassment and assault, particularly in the workplace and directed towards women. Obviously, the hashtag went viral via social media platforms like Twitter and Facebook, while physical protests surrounding this issue were also held throughout the country, naming perpetrators of these crimes and triggering controversy. As you can see in the interactive image above, it is oftentimes celebrities with large follower counts that get retweeted over and over again, resulting in more awareness of the issue, while twitter users with very low follower accounts don’t seem to generate nearly as much awareness. Although this might seem obvious, it is valuable to know that, in this day and age, celebrities truly do hold lots of power outside of the market and the state: but this power seems restricted to the virtual realm. 

I conducted a survey, “#MeToo: Virtual & Physical Protest,” and received about 40 responses that answered questions about primary sources of news and political influence beyond simply Twitter. 

Respondents were asked to identify their primary source of news, choosing from options of television programs (like CNN, BBC, Fox News, local news, etc.), newspapers (like the New York Times, the Wall Street Journal, local newspapers, etc.), social media platforms (like Facebook, Twitter, Instagram, etc.), or word of mouth. Respondents were also asked to recall the first time they heard about the #MeToo movement and the source of that information. Many of the respondents reported that they used social media as their primary source of news, and 13 of those 21 people first heard about the #MeToo movement from the use of the hashtag. Surprisingly, there were people who receive their news mostly from watching television or reading the newspaper and yet first heard about the movement via its associated hashtag. This might begin to suggest that the virtual movement was stronger and more influential than the physical, conventional, and professionally-documented demonstrations. Refer to the graph below to see the information gathered from the survey.

Many of the survey respondents--twenty-one to be exact--cited social media as their primary means of receiving news. Determining exactly which social media platforms each survey respondent have accounts and are active was therefore an important follow-up question. The following diagrams show that 100 percent of survey respondents have Facebook accounts, but only about 60% consider themselves most active on the platform. Other popular platforms include Twitter (64% with accounts, 20% active), Instagram (90% with accounts, 51% active), LinkedIn (77% with accounts, 7% active), Snapchat (56% with accounts, 15% active), and more. 

So far, the implication of these survey results is that, for the #MeToo movement, virtual demonstrations have been more effective than physical demonstrations. But it is worth noting that of the 39 respondents, only 10 reported that they had attended a protest. Is this due to their perceived ineffectiveness? According to respondents, this isn’t true: as the graph below shows, the majority believe that physical protests (strikes, marches, parades, picketing) can be equally as effective as virtual protests (hashtags, viral posts) in terms of spreading awareness of an issue. In terms of achieving consensus--an important distinction--the majority of respondents still believed that both physical and virtual protests could be equally effective.


There are quite a few limitations to this research I’ve conducted. First, it was difficult for me to locate datasets with information that corresponded to tweets, favorite/retweet counts, account name, follower count, and participation in a physical protest. Ideally, I would have compared the influence of tweets by people who physically attended a protest to the number of people who were made aware of the movement via, say, television coverage of a physical protest. Additionally, I am extremely inexperienced with the software required to do these complex analyses, so there were many technical obstacles about which I was not sure how to maneuver. Lastly, the number of respondents to the survey I conducted was vastly different from the number of datapoints provided by the two sources of Twitter data I used, meaning that the percentages could be inaccurate. 


I hope to rectify the number of respondents to the survey to better compare between virtual and physical protest influence as well as evaluate tweets for negative and positive reactions to the #MeToo hashtag, similar to the “We Feel Fine” project. 


For activists, it seems imperative to be cognizant about the approach to organized protest in the virtual realm. Influence and awareness are, of course, primary objectives, but it seems that scaling up the conversation—meaning adding more voices via original tweets from twitter accounts with low follower counts—does not do as much to help the cause as thousands of retweets from a celebrity does. 

For architects and journalists operating in physical or non-virtual realms like television broadcasts and newspapers, it seems to be effective to unite the physical realm with the virtual; however, this connection should happen outside the domain of the state and the market. Bottom-up, citizen-led initiatives rely on a truly public forum that might only exist in a virtual realm, so learning from this contemporary space for dissent might prove fruitful. 




ASSIGNMENT: imagine a future dystopia placed on the studio class site

With the widening gap between upper and lower classes, our future urban condition is shaped by a space race of sorts, with the wealthiest individuals of society racing to build taller and taller structures in order to control more elevated terrain. This vertical race is compounded by the relaxing of building codes on height restrictions in most urban areas, intended to achieve higher densities and encourage a culture of micro-housing; however, this lack of restrictions only helped the wealthier class, diminishing the value of land on the ground plane. Living conditions become almost unbearable, without the ability to farm due to shading from the buildings above, the continued problems with flooding on the ground plane which were never solved, and spillage from the elevated planes above. Life above the canopy is blissful and perfectly conditioned, almost an exact copy of the original ground plane and inhabited exclusively by the wealthiest classes, who are constantly engaged in cutthroat competition to build taller structures for bragging rights. These people are incredibly ignorant of life on the ground plane, unaware of the devastating effects of the canopy to the environment beneath them.


Penn State BArch Program, Third Year: Furniture Gallery and Studio (1 week)

Awarded First Honor

The late Bill Hajjar, a prominent local architect and former studio professor at Penn State, is well-known for leading the movement of mid-century modern design in central Pennsylvania. It was on the property of one of his more prominent projects, the Eisenstein House, that we were instructed to design a small gallery with attached workshop to display and restore mid-century modern furniture.

When curating an exhibition, the primary goal is to create an environment that inspires, organizes, & advertises the collection. I was intrigued by this small gallery’s ability to provide a look into a past time. The gallery provides this vignette of a zeitgeist by carefully composing an arrangement of restored furniture in a monolithic form that removes visitors from “the now” and places them in a blank, vacuous space. In order to intrigue passersby, a single window with a featured furniture piece hints at the contents of the gallery, serving as signage for the somewhat obscured building. The simplicity of the block with a single window display creates a compelling vignette of a past time.

The reading room is somewhat of an extension of the mood of the gallery, providing a space for reflection. Being buried into the site, with windows above the seating area, visitors are again immersed into their thoughts of another time.

The studio portion of the program had to be treated differently than the gallery and reading room. Here, creation, production, and activity encourage passersby to take a closer look. The form of the studio, then, deserved abundant transparency to display the activity of restoration.

All the pieces of this small building serve to provide a small glimpse, or a vignette, of mid-century life through design.

With a little too much time over a winter break, I co-opted an old rendering to create a holiday card from my studio group so I could experiment with snow textures.