Woody Allen Love NYC


Visualization

Introduction

The topic that I chose for this Carto lab is ‘Woody Allen Love NYC’. The reason why I choose this topic because I saw so many his movies shot in NYC, they may give me the first impression of this city, and even though every movie could tell different stories. However, I still want to see these place in real life. Like novel fanatics want to track their writer’s step, I want to see how movie depict a city with locations.

I love to choose art products data, not only for me myself like them, on the other side, I want to explore the story from various angles.  The idea came from an article: On Close and Distant Reading in Digital Humanities: A Survey and Future Challenges. Distant Reading could generate an abstract view from observing textual content to visualizing global features of single or multiple texts.[1] Moretti [2] describes distant reading as “a little pact with the devil: we know how to read texts, now let’s learn how not to read them.” This time, I try to combine “near watching” and “distant reading” in Woody Allen’s movies. Give people who love movies an interesting direction to explore after they saw the movies. Also, from this map, you could see what kind of location Woody Allen prefer.

Materials

I create this visualization by Carto as the primary software. It provides GIS with several data layers without coding. It’s simple to use and also beautiful.

In terms of data, the basic sources are from NYC Open Data. And the location of movies came from The World Wide Guide To Movie Locations. This Website mainly by the film lovers capture movies sightseeing and write it down. Since the article describes locations orderly, I collect them orderly according to the development plot of the stories.

  1. NYC District Zones(Polygone)
  2. NYC Park Zones(Polygone)
  3. NYC Museum Location(Spot)
  4. NYC Theatre Location(Spot)
  5. Woody Allen’s Movie Locations Which shot in NYC(Spot)

(Blue Jasmine; Everyone Says I Love You; Hannah and Her Sisters; Manhattan; Whatever Works; Café Society; Hollywood Ending; Celebrity)

Target Groups

My target group is people who want to know more details or who want to change a perspective to movies. Especially movie fans and major person.

Inspiration

For my visualization, I went through various dynamic geographic visualizations. For me, dynamic and interactive visualization is only a form for people look at things in an active and vivid way. But because of that, people could create fantastic stories in terms of life better.

“How Fast Your City Runs” is an interactive map for 2016 Berlin Marathon. With this dynamic map, users could follow the Berlin Marathon in time lapse for the first time, and compare the runners. It shows the speed of 35,827 runners that finished the 2016 marathon ran through the city. Each individual runner is animated as a redpoint on the map, using the real running times, the dynamic dots also could be filtered according to gender and nationality. In addition, the runner can enter their personal best time and track their position on the map, alongside the average for the field. If this application systematically, marathon runners all over the world could track their own growth and do better analysis.

The map is supplemented by an aggregated ranking for runners from a particular Berlin district, German state, or country.[3]

Eric Sanderson and his colleagues try to discover the ancient time of NYC. What they did is not only georeference the old map into today’s grid but also try to remove the artifact concrete buildings in this city to find NYC’s ecological fundamentals. Based on the creatures and environment need, they create a data social network, the network of all the habitat relationships of all the plants and animals in Manhattan. 

The Muir Web(name comes from John Muir)

People could compare the old landscape and today without judge which is better but learn from the sustainability of the past, of the original ecology, of nature with all its parts. They extend this idea into creating a landscape of 400 years from now, in an ecology way.

habitats for people, and need to supply what people need: a sense of home, food, water, shelter, reproductive resources, and a sense of meaning. This is the particular additional habitat requirement of humanity. And so many of the talks are about meaning, about bringing meaning to our lives in all kinds of different ways, through technology, through art, through science, so much so that I think we focus so much on that side of our lives, that we haven’t given enough attention to the food and the water and the shelter, and what we need to raise the kids.“[4]

Mannahatta of 2409

A Distributed Denial of Service (DDoS) attack is an attempt to make an online service unavailable by overwhelming it with traffic from multiple sources. They target a wide variety of important resources, from banks to news websites, and present a major challenge to making sure people can publish and access important information.[5]

This map shows DDoS in a worldwide range, people also could track the dynamic map by date, type, and nation…From various attacks, such as “CC attacks, SYN attacks, NTP attacks, TCP attacks, DNS attacks, etc.” Now that DDOS is becoming more and more terrible, NTP attacks are becoming more and more mainstream. This means that per second Attack traffic amplification hundreds of times, such as 1G SYN fragmentation attacks into NTP amplification attacks, it becomes a 200G or more.

Methods

Firstly, I choose a dark color as the base map, and uploaded NYC regions dataset and change the value of color, then I add Movies Location/ Theatre Location/ Museum Location and Park Properties. I change the order of different layers(Top-Bottom: Movie Location – Museum – Theatre – Park – NYC Region). For separate Museum and Theatre, I use black polygons to display Theatre Locations, and white point to show Museum Locations. At first, I want to show the overview of Woody Allen’s all NYC movie locations. So I colored by movie’s name, georeference by longitude and latitude, add the label of movie’s name and apply the auto style. So I get the graph:

Then, I want to divide location by movie and show the dynamic movement of each movie. In this case, I changed style – aggregation into animated. People could track characters step by step in this way.

I add Click pop-up to show my movie database’s data. Give the person who wants to go these places a basic information.

Results/Discussion

The visualization can be viewed here.

It’s interesting to notice, Woody Allen’s earlier period of movies, like Manhattan and Annie Hall, very like to choose midtown of Manhattan as shot space, with lots of overlap with theatres and museums, also parks. Recent films, like Blue Jasmine, Whatever Works, and Caffee Society, he is more get the touch to other places, Queens and Bronx, Uptown…But art places and sightseeing is always his choice.

Future Direction

In a nutshell, Carto is easy to use with lots of fun to work with and the pattern is concise. However, I could only show 5 movies title on the label with colors. Also, the database needs clean and with specific longitude and latitude, which is not very convenient for every dataset.

I believe my theatre and museum layers are not good to look and seem a little noisy. And I will probably add more information(such as Specific theatre’s open and close time) for people who want to visit these places. I want next time use more analysis for different kinds of datasets.

 

[1]Jänicke S, Franzini G, Cheema MF, Scheuermann G. On close and distant reading in digital humanities: A survey and future challenges. Proc. EuroVis, Cagliari, Italy. 2015.

[2]MORETTI F.: Distant reading. Verso, 2013. 2

[3]“Berlin Marathon 2016 – How Fast Your City Runs.” Online Journalism Awards, awards.journalists.org/entries/berlin-marathon-2016-how-fast-your-city-runs/.

[4]Erson, Eric. “New York — before the City.” TED: Ideas worth spreading, www.ted.com/talks/eric_sanderson_pictures_new_york_before_the_city/transcript#t-840997.

[5]“What is a DDoS Attack?” Digital Attack Map, www.digitalattackmap.com/understanding-ddos/.