Technologies of Text (S12)

     Ever heard the saying “a picture is worth a thousand words”? Well Nathan Yau truly believes in this for he focuses on his work and his tweets on effective ways to transform what would be textual data into graphs, pictures, and in this case maps! I know this sounds like I am mocking one of the books we will be reading, Graphs, Maps, and Trees by Franco Moretti, but Yau recently tweeted about Watercolor Map Tiles. This article tells about how interactive maps, heavily designed by Stamen Design have been improved from maps that simply used the color “yellow.”

     A link I encourage you to follow, interactive map with watercolor map tiles, from the original link shows the cleverly named town of Stamenfrom three different perspectives: terrain, toner, and watercolor. Toner is ” high-contrast B+W (black and white) maps [that] are perfect for data mashups and exploring river meanders and coastal zones.” You can also choose between three “flavors”:  normal, no labels, only labels. Terrain is described as, the way to best “orient yourself.” The terrain maps featur[e] hill shading and natural vegetation colors. These maps showcase advanced labeling and linework generalization of dual-carriageway roads..” Yet the innovative technology that helps demonstrate the city of Stamen through computer generated images that look  ”hand-drawn by a skilled artist slash cartographer” to show “organic edges” and give texture to the map.

watercolor, toner and terrain... check it out!!

    This technology reminds me about the other mapping technology we have learned about previously in th semester of “Advanced technology similar to Google Earth, MapQuest and the GPS systems” in the article, Geographic Information Systems Help Scholars See History. Not only does this new Stamen technology help give information about the place itself but it also displays the useful thing that graphs and maps can tell so much about a certain something can be said with little or no test. I believe that this effective presentation will play a role in not only the future of digital humanities but the world in general.

After working with word clouds the last couple of days, I have come to realize that they are actually helpful.  At first, I wasn’t sure how such a thing could help someone understand a long novel without having to read the entire story.  But now, after the lab assignment for this week, I’m a believer.  By observing the most frequent (uncommon) words included in the novel, I was able to get an idea of what the novel was about.  Instead of having to read all 135 chapters, I was able to spend only about an hour or two, using Wordle and Voyant, and still was able to analyze the relative word frequencies to help understand what the novel is about.

I find this form of “not reading” to be a very interesting style of research and comprehension.  This reminds me of the “Infographics” blog post by Matt Evans a few weeks ago.  At first, it was difficult for me to understand how word clouds would help me understand a novel without reading it.  But now, I can see how some people would rather just look at a word cloud to interpret a text rather than physically reading it.  This is similar to infographics because instead reading text to pull out data, infographics allow readers to analyze and interpret information in a more visual way.  I think infographics, word clouds, and other visual forms to interpret text are starting to become more and more common to the average reader.

The following link shows how useful word clouds can be.  If someone wants to know the topic(s) of debate, for instance, they can identify these topics fairly easily from a word cloud.

http://www.journalofamericanhistory.org/projects/lincoln/media/pinsker/documents_artifacts/word_cloud.html

Word clouds are just another example of how digital humanities is changing and how digital humanities is changing our society.  The question of whether these are good changes or bad changes is a separate discussion, but I don’t think there is any debate that digital humanities has a significant effect on our culture today.

A lot of studies claim to work with data; studies like Math, Economics, Computer Science, Physics, and many more.  As for digital humanities, it’s the new kid on the block and isn’t always taken seriously. I recently read an article on the Inside Higher Ed blog that asked the question: why isn’t the digital humanities being taken seriously? A lot of people look at the digital humanities as another field that mines data and comes up with a few answers.

Noah Wardrip-Fruin , the writer of the article I read, states:

“Why is there the stereotype that, while computer scientists and digital artists have much to discuss, digital humanists only want to talk about data mining with the former and data visualization with the latter?”

In class, we have not done any serious data mining until this week. We have however been aware that this is an essential part of the digital humanities through twitter and the class blog. In the conversations I have seen on Twitter this semester, it does not seem like that is the case with digital humanists. They seem enthralled in both data mining and data visualization with anyone.  As a non-digital humanist, I have always felt that the conversation covers both aspects mentioned above.

The article goes on to talk about how modern life is driven by hundreds of computer processes from Microsoft Word to phone apps to Walmart’s procurement systems. So why are the Digital Humanities that important? The answer is that digital humanities’ processes help us understand historical texts and events in order to better adapt to the future.

Rather than the stereotype of digital humanists preserving texts and managing databases of books and articles; digital humanists are helping humanity through processes that might not have applications yet. Is this a waste of time? Clearly not, the digital humanities has over 100 centers and have ever increasing funding. So, as a student who is dipping into the digital humanites conversation, I am finally beginning to understand exactly where the digital humanities fits into the academic world.

Read more: http://www.insidehighered.com/views/2012/03/20/essay-digital-humanities-data-problem#ixzz1pmAW33ly

I saw an interesting article posted by IDEA.org on twitter that I thought fit nicely with our discussion on textual analysis. People who work in the English discipline have struggled with identifying the birth and death of words. There has been an interesting project taken on by some physicists who used Google’s database for their work. Within their paper they named this field of study, Culturomics. In order to do this study they included people such as evolutionary theorists and members of Google. The evolutionary theorists played an important role in analyzing this as an “evolutionary word world”.

They attempted to estimate the true number of words that exist within the English language and came up with a million. This is very different from what have been seen elsewhere. For example, Webster records 348,000 words. The words not found the dictionary the authors termed as “dark matter”.

Their next step was to track the usage of those words. They analyzed the different forms of words we use, such as sneaked versus snuck. They also tracked the importance of themes within literary works , such as history. The importance of history in writing has decreased. In books, it took 32 years after 1880 for the term to be referred by 50% less. For 1973, it only took 10 years.

They also used the database to analyze languages such as Spanish and Hebrew. They studied the birth and death rates of words. They determined last year that English is growing at a rate of 8,500 words per year. They now believe the growth is slowing because the marginal benefit of adding new words is declining due to mass of words already established. They see an increased death rate due to homogenization. This is partly due to technology’s impact on words. Using things like spell-check homogenizes individual’s spelling. Their final determination is that a word’s future is determined in its first 30 to 50 years. At that point, they will either carry a long-term weight or die off.

The group says that Ngrams, the program we’re using for this weeks assignment, is key to Culturomics.

http://books.google.com/ngrams/

A lot of people choose warm destinations for spring break such as Florida or California. I, on the other hand, chose Colorado. Three friends and myself set off to the great state last Saturday morning by car. We said screw the warm weather, lets go snowboarding. On the 18-hour car drive I thought about the Technology of Text class and Walden. I wondered how long I could make it without using my laptop or cell phone. So, when we got to Colorado, I turned off everything. I didn’t use anything the first night however, for safety precautions, I left my phone on in my coat in case something happens to me or one of my buddies when we split up. Afterwards, I turned my phone off and my computer stayed put in my luggage. I usually use my phone as my alarm clock however, while on my trip, I relied on my friends to wake me up in efforts to not use my phone.

On the third day, my dad left me a voicemail and told me he sent me an e-mail (3 days ago at that time) and was wondering why I wasn’t responding. I told him what I was trying to do and apologized. I finally opened my computer for the first time on the trip and his email was pointless. It was one of those “parent e-mails” that just ask how everything is and make sure I was okay. After reading this, it put a smile on my face that I hadn’t used my computer because I already know my parents worry about me, I didn’t have to read e-mail after e-mail about it. During this quick time on my computer, I checked my Facebook page because, to be honest, it was just too temping. I checked my notifications, scrolled down my newsfeed, and added a picture or two of the trip so far and logged back off. That was the first and last time I used my computer on the trip.

The phone on the other hand was a lot harder to not use. When you have three other friends there and the mountain is closing, you need to figure out where they all are and how to get to them. Also, at night, when we are out and about at bars and some of us go wandering, it’s nice to leave/receive messages about going back to the hotel. So, as a recap, I didn’t use it for the whole car ride there or back, I turned when we went snowboarding and then turned it back off until night when we went out.

In the end, I think I did a pretty good job not using the technology available at the time. I only used my computer once, and while I thought about blogging while there during my free time, I thought that would be “cheating” on my mission. Overall, I actually found it enjoyable to not have my phone going off and being obsessive about Facebook notifications all week. It’s odd to say, but Thoreau definitely was right. By turning off all my electronics and because I stopped worrying about what was going on around me, I was more relaxed than I have been in a long time.

This week’s topic of data mining instantly reminded me of one of my favorite shows, The Colbert Report. During Paul Fyfe’s guest lecture, he brought up the idea of data mining by means of using a word cloud. The clever idea of using a word cloud to analyze text is not only useful but quite entertaining. While campaigning for his “Colbert Super PAC”, Steven Colbert explains how he reached out to his followers giving them a chance to express what is important to them. He received over 53,000 responses and even though he promised to individually read each one, he used a “Persuadulux 6000” to form a word cloud to organize the reoccurring words in the responses.

 
For me, this clip couldn’t better exemplify what we are doing with this week’s material. Colbert cleverly uses sarcasm to show how impractical it would be for him to physically read each response. He also, briefly explains the idea of a word cloud and has some fun with the results.

 
Once he has his word cloud he makes some modifications by singling out only responses in which people were willing to spend a dollar to speak their mind. As he finds out, the results are drastically different. Lastly, Colbert sheds light on the fact of actually interpreting the word cloud and what it could possibly mean by brining in an “expert in the field.” The actual interview with the expert, Frank Lutz, is extremely humorous and is in the second link posted. Colbert cleverly provides a perfect example of how not to use buzz words and how interpreting them can be mistaken. I highly recommend taking a minute to watch these videos when considering Monday’s discussion and this week’s assignment.

 
Persuadulux – 6000
http://www.colbertnation.com/the-colbert-report-videos/394776/august-16-2011/colbert-super-pac—persuadulux-6000
Frank Luntz Interview

http://www.colbertnation.com/the-colbert-report-videos/394777/august-16-2011/colbert-super-pac—frank-luntz-commits-to-the-pac

http://gawker.com/5893115/school-assembly-devolves-into-surprise-anti+gay-anti+choice-bash-fest

So, remember when we had those motivational speakers or assemblies in middle and high school? Everyone is always super excited to get out of class for a little while at the least, but most of the time, I was actually excited for what this assembly was going to be about because they were usually pretty interesting and fun. I had never gone to a bad/boring assembly in all of my years but after reading this article that tweeter Danah Boyd shared with the world, I was definitely glad I didn’t go to that assembly.

It was supposed to be a presentation about bullying and making good choices, but more or less turned into a persuasive speech on why you should hate gay people and how its anti-christian. I could not believe some of the things these guys said in that video I attached. These kids are just at the right age where the topic of homosexuality is brought up more than often, and usually in a negative way, so to have persuasive speakers talk about it in a negative light as well just pours gasoline on the fire. I feel so horrible for the kids that happened to be homosexual and had to sit through that and probably hate themselves even more than they already do for being confused about their sexuality.

The school administration was not aware that this group was anti-gay and the school even called other schools that the group had made appearances at, and nothing was ever mentioned. Some kids even got up and left during the performance and got boo-ed and yelled at for their actions. That is honestly what I would have done and I would have encouraged other people to do the same thing. I am wondering why the school didn’t stop the assembly as soon as things took a turn for the worse. It’s not rocket science.

My question is, what’s with this group being a christian group?? As a christian myself, I was always taught to love my neighbor, and this is FAR from that. The bible doesn’t condone homosexuality but from what I know, it definitely emphasizes to love one another more.

This week’s discussion of text analysis was a relatively familiar topic for me, because one of the blogs I follow for this class is about text mining. On this blog, Aditi Muralidharan discusses her text mining research of Shakespeare’s works. She uses a program called “WordSeer,” and provides videos of it being used so you can visually see how the research is done. “WordSeer” can show the frequency of words appearing in texts, how specific words are used in context with others, and compare different texts. Using this program, Aditi can try to answer questions like, ““How does the portrayal of men and women in Shakespeare’s plays change under different circumstances?” or “How is the word loved used differently in tragedies and comedies?” You can go to her website “Text Mining and the Digital Humanities” here.

I wonder what would happen if you were to analyze all of your Twitter feeds from the past week, month, or semester? Would you find that words used the most would be related to events or people? I’m not sure, but it would be interesting to try.

I had never heard of analyzing text through text mining, word clouds, or other such things before this class. At first these processes seemed kind of frivolous or excessive. But, I can see now how they provide a different perspective to textual research, especially when a large amount of materials is being used. I liked the idea of using these kinds of programs to see how certain words have peaked and diminished in use over time. This reminded me of an online comic that I sometimes read called “Lackadaisy.” There was one extra strip where the characters used some 1920′s slang, and now many people have no idea what it even means anymore. You can find this comic strip here. If you want to go to the actual online comic website, click here.

On another note, can you believe the weather we’re having?! It’s so beautiful out, but I’m afraid for another cold spell that will kill all the new buds & sprouts.

Believe it or not,  I have been crossing several word clouds more frequently in the past couple weeks than usual. I’m sure you can imagine my excitement when I found out we were going to be carried through a website that makes word clouds with Paul Fyfe today.

So when I’ve been following another class, similar to ours,  on Twitter lately. Their digital humanities class seems to have covered similar digital topics to ours, but their professor’s latest blog post was about word clouds! How exciting! I highly doubt their class had the opportunity for a virtual tour of Voyant, but it seems for once we’re talking about the same thing at the same time.

Anyways, I really enjoy breaking things down.  Not only do I find that sometimes another layer of meaning can be found, but also maybe the core meaning can be exposed by breaking things down to their fundamentals. I find it interesting to break websites, blogs, texts, chapters down to their words- where you can look at either the well selected diction the authors used, or the frivolous, repetitive words that eventually carry less meaning. I had some fun breaking down some of my blogs (often frivolous repetitive words) from study abroad as well as looking at an Aristotle word cloud example posted on the aforementioned blog.

Not only breaking things down, but looking at things (in general, and in the textual context) on a different scale can add a whole new layer of meaning and give depth to what you’re looking at.