After many thoughts about what to chart and map using the Google Fusion service, I decided to document some of the cities I visited this past summer during my study abroad adventure in Germany. I mapped the various cities and their populations. I was curious to see how many people live within each city after visiting and experiencing them. Each category links to the original charts.
Here is an overview of the ten cities I visited or traveled through. I included the city name, country, an image, and the geographic location with latitude and longitude coordinates.
I looked at the top 20 Twitter accounts with the most followers and chose ten of them [mostly because I wanted Ellen Degeneres on my list and she wasn’t in the top ten, but also because the YouTube and Instagram accounts were in the top ten and I didn’t think they would be as interesting to track] for this project. I recorded each person’s name, picture, occupation, their follower count [as of Thursday], the number of years they have had their accounts, and what city they live in primarily. Each label is a link to the original chart in Google Fusion Tables.
Using Google Fusion Tables, I explored commonalities between 1990s sitcoms because they all followed a similar storytelling formula. Looking at 10 shows, I mapped out the locations of the settings for each show, finding that nearly all of them took place on the east or west coasts. The pie chart reveals the number of shows per network and the bar graph shows its data points comparatively. What’s most interesting to me is the network view. The connections between broadcast/cable network and series is a more visually engaging way of sharing the information. http://wp.me/p4UATe-fk
Data CardsWhere in the world were these shows taking place?Number of Shows per NetworkA Look at Number of Seasons in a Series and Number of Main CharactersConnections Between Network and # of SeasonsNetwork View (Literally) of Series’
You can find interactive versions of these visualizations here, and my spreadsheet can be found here. (I added the “Genre” section after I made the spreadsheet directly into Google Labs)
The card set for my data (both of the above)The map from my dataThe bar chart from my data, which shows the amount of main characters in relation to what movies they are from.My network visualization, which shows the genres of the movies and how they are connectedA bar chart, which shows the amount of main characters over the years of the movies being made.
For a change of pace, I read the Sherlock Holmes story, “The Adventure of the Dancing Men,” from Sir Arthur Conan Doyle’s The Return of Sherlock Holmes collection. I used the Voyant word cloud tool to visualize the story. The first version featured the words “holmes,” “mr,” and “mrs” that I deemed unimportant to the story. I realize now that, though “holmes” is a bit obvious and takes up a lot of room, the other words I listed indicate relationships which may be important to the overall story. Please bear this in mind as I continue without “mr” and “mrs” (because I took this screenshot on a different computer that allows screenshots and so I will be using this visualization):
The loss of “mr” and “mrs” may not be so terrible, after all. These “words” don’t modify any others to indicate which name they belong to, which I believe is a fault of the word cloud. If I were looking at this visualization and trying to find character names, they are spaced throughout and it is impossible to determine which first name goes with which last name, or if each name is even related. However, one can see that “husband” and “wife” are featured in the word cloud, so a marriage is implied. “Norfolk” also shows the setting of the story. While some related words point to a plot line — for example, “bullet,” “shot,” and “fired” suggest that a character has been or will be shot in the story — other related words like “man,” “men,” and “face” fail to create an image of just what the “Dancing Men” part of the title means. In reality, the dancing men are drawn stick figures used as a code to send messages to one of the characters.
The word cloud has the potential to give the viewer a lot of information about a document, but in some cases it may fall short of its purpose. The words used in this word cloud are no true representation of what occurs in the story. Looking at the picture, I can see that there is a husband and wife, a few named characters, a setting, a letter, and someone gets shot. This does not answer the question of who the dancing men are and, since the story is named after them, this is a lot of crucial information not being relayed.
Though I like the aesthetics and intention of the word cloud, I can understand why some people would be opposed to its existence, like Jacob Harris from the “Harmful” article we read seems to be. A narrative may be impossible to find in a cluster of frequently used words with no specific meaning; therefore, the word cloud may not be effective or properly convey the meaning of the document it represents.
Many people hold word clouds, wordle in particular, in a negative light. While I agree that, yes, sometimes word clouds can complicate things more than they clear things up and make posts look messy, if done correctly they can be quite useful.
Above is a word cloud of the short story A Scandal in Bohemia, by Arthur Conan Doyle. I used wordle to create this visual because I knew how to work it and I found it was best suited for what I wanted to do. If someone were to look at this word cloud, they would already know that the story was about Sherlock Holmes, a king, and a photograph because those are the biggest words in the cloud. The black and white color scheme makes it easier to read because the black words stand out against the white background. I enjoyed picking which font to use, though it was frustrating because a lot of them were very hard to read. I picked this font because I felt it had more of a Victorian feel than any of the others. So, right off the bat, someone would already know that this Sherlock story was about a king and a photograph, and also, if he was using his context clues, that it was written a long time ago.
I think word clouds are best left to help someone get a basic understanding of a book or of an idea, not to be used in a serious argument unless it is absolutely necessary. All and all, there is a time and a place for word clouds, and if you’re a beginner with web tools, wordle can be very useful.
Before I created my own word cloud, I read the two blog posts regarding this visualization aid, and although one went more in depth about different websites where word clouds can be made, the blog “Word Clouds Considered Harmful” (well, the title says it all) had a very negative attitude toward these fun and light-hearted artistic creations. However, ironically enough, when I was searching for the definition of a word cloud in Google it came up as “An image composed of words used in a particular text or subject, in which the size of each word indicates its frequency or importance.” I found this interesting because in the negative post about word clouds Harris talks about how the size of a certain word should not emphasize the importance of it; but Google seems to think otherwise. Although I do not necessarily agree with Harris, I do believe that before people engage in making word clouds, they should read and understand the text that is being artistically manipulated. With this being said, more people would stray away from using only a word cloud to understand texts, and focus more on comparing their recent finds along with the finds of a visual aid.
Regardless of everyone’s opinions on word clouds and the significance in making them, I actually enjoyed customizing my word cloud for my favorite Sherlock Holmes story, A Scandal in Bohemia. At first I had trouble with Wordle (because of Java) and I decided to try Voyant. However, after seeing what my word cloud looked like with Voyant, I realized I was more of a Wordle fan. When I created my first word cloud with Voyant, many of the words that probably should have been emphasized, were not. For example, Holmes, Adler, and women were not even included in the word cloud. Secondly, I found that a lot of common words had the most emphasis and when I tried to take those out, it didn’t go as planned. Therefore, I tried Wordle again and after downloading Java, I copied and pasted my text and created the word cloud pictured below.
Here is my word cloud with my customized color palette and font. Do you think Holmes would be proud?
As I played around with Wordle, I found that I enjoyed being able to customize my visualization based on my preferences. As I kept clicking ‘randomize’, I gained insight on what shape I wanted my word cloud to be, the positioning of words, the color scheme, and the font. After it was all said and done, I chose to create my own color palette because I felt like the basic palettes were overused-so why not create my own? When I created my palette I chose dark colors so that words would clearly standout. My colors ranged from different shades of purple, a dark blue, a red wine, and a dark green, just because I found those most appealing. After choosing the specific colors I wanted, I chose to view the different fonts. After viewing various ones, I wound up using a font that made all the words neat and legible.
When I started to analyze my word cloud based on my prior knowledge from reading A Scandal in Bohemia, and understanding what word clouds are used for, I pretty much agreed with the words that mad most emphasis in the word cloud, versus the words that did not. For example, Holmes was obviously the most emphasized because he is a main character not only in this story, but also in all Sherlock Holmes stories (no pun intended). Another word that had emphasis was photograph. As readers know, a major theme in the story is the lost picture and is the main cause of stress for the king or ‘majesty’ (also emphasized), so it makes sense that it is one of the larger words. One thing that I did find interesting was how woman was not emphasized. I understand that ‘woman’ may not have been said a lot in the story, however it is a major representation of what Holmes thinks Adler to be and readers should know of regardless.
What did you all think of word clouds? Yay or nay?
Using the Voyant tool, I made a word cloud of Sherlock Holmes’s adventure, “Scandal in Bohemia.” It is unfortunate that the tool does not utilize color to distinguish word frequency or other significant word trends because that would have allowed for some interesting insights. In any case, the word size was telling enough to extract some Sherlockian observations about the context of the story. In my generated word cloud ( http://voyant-tools.org/tool/Cirrus/?corpus=1411164560979.4726&query=&stopList=1411165833459tu&docIndex=0&docId=d1411099477875.99b8b096-b231-7094-d527-8b986fefb364), the most to least significant elements of the story are apparent from larger to smaller size. ‘Holmes’ appears 47 times, ‘photograph’ appears 21 times, ‘king’ (17), ‘majesty’ (16), ‘irene’ and ‘adler’ (13), and ‘woman’ (12). It’s no surprise that these four aspects of the story surface most frequently and the the photograph can be considered a tertiary character of the story because it is crucial to the reveal and the idea of ‘the woman.’
What I took most note of, however, was the lack of Watson’s name. Holmes is obviously the largest word, front and center, but Watson is notably smaller and on the outskirts of the cloud. His name appears 6 times, half as many times as the mention of Irene Adler’s name. Though this does make sense because he is the narrator and therefore is primarily mentioned in the first person in the text, I expected to see more of his name when Sherlock addresses him in conversation. A conclusion from this ‘where’s Watson’ is that this is a subtle show of Sherlock’s narcissism. Holmes’s heightened perception and memory are arguably the biggest parts of the story, but his lack of addressing Watson – our narrator and the right hand man – by name is a way of noticing Sherlock’s ego from a quantitative perspective.
Word Clouds are graphic visualizations of the most frequent words used in a text. This tool allows fresh interpretations to be made about any texts. It provides a unique way of looking at a cluster of frequently used words that may elicit a different understanding of what is being presented.
I chose to closely read The Adventures of Sherlock Holmes: The Blue Carbuncle and create a Word Cloud to develop a new understanding and a fresh perspective on the story. I used Voyant as a tool to generate a Word Cloud for the text.
After editing the stop words and removing irrelevant words, the most common words to appear in the text are: man, holmes, hat, goose, little, know, stone, bird, and geese (beginning with most frequent word). These words make sense considering the premise of the story involves an investigation of the missing blue carbuncle in the neck of a goose. However I feel that this visualization and understanding of what is most important and valuable in the text would benefit from excluding similar words such as “goose” and “geese” and “bird”. I will edit the stop words to take away “geese” and “bird” and a few other less frequently occurring words that seem to be duplicates in one way or another to see how it strengthens my observation. In the new Word Cloud, there is a stronger sampling of frequent and presumably important words. The most frequent words are: man, holmes, hat, goose, little, know, stone, just, sir, baker, and tell. These words are a little more precise and reveal a lot about the plot of the story.
A quick browse through the word trends shows some information about where words more frequently appear in the text. The most frequently occurring word “man” appears scattered throughout the text in an even fashion. This makes sense since it is such a generic word. The top three words used commonly at the beginning of the text are: hat, goose, and stone. The top three words used more towards the end of the text are: holmes, little, and know. If I had no prior knowledge of the story I would analyze this information as a story starting out confidently and ending up a mystery. There seems to be a clear understanding with these frequent words that the beginning of the story is set up in such a way that is confident and outlining the premise. There are strong nouns that identify the main points and symbols of the story. It highlights what is most important. As the story progresses there are mysterious things happening. A case is being investigated by Holmes. The frequently used words that appear more often towards the end of the story are Holmes (noun), little (adjective), and know (verb). Holmes is solving the mystery of the Blue Carbuncle so naturally one would expect his name to appear at the end or resolution of the story. Interpreting the words as “Holmes knowing little” is another angle that could be looked at. Even though he does solve the case, the majority of the story is all about clues and small bits of information that are used as a collective whole to solve a mystery. These words and their placement in the text may be valuable in understanding the key points and themes of the story.
Using the Word Cloud platform and Voyant tool to analyze a Sherlock Holmes story is a fun and interactive way to read and understand the text. Being able to control what words should or should not appear in the Word Cloud, viewing the word trends, and seeing the frequencies are all helpful and can be used to extract important symbols or themes in the text that may have otherwise gone unnoticed.
Digital Humanities at the undergraduate level is huge at other universities. Check out UCLA’s description about DH:
“Digital Humanities interprets the cultural and social impact of new media and information technologies—the fundamental components of the new information age—as well as creates and applies these technologies to answer cultural, social, historical, and philological questions, both those traditionally conceived and those only enabled by new technologies.”
There are lots of cool courses that show how DH is growing at colleges: http://www.digitalhumanities.ucla.edu/
