Final assignment for Quant Humanists and Nature of Code.
Continued from the last exercise: detecting those titles with Korean letters was easy but excluding them wasn't. I asked help from Allison to figure out how to filter out the ones with Korean, which is a method that ideally only collects English titles.
The problem was, sometimes I visited contents that belong to neither Korean nor English. After the review, I found out mostly they are Japanese, and excluded them as well - despite of their small number.
Next step was going into more details. One of the things I tried was checking the usage difference of same service in two languages. It will be more useful if I can collect interesting keywords, and filter out results based on them.
Include a quippish timeline of your reflection "thesis statements", and design a way to represent your mood throughout the course.
While thinking about different ideas, I kept collecting my ip information. One of the things I noticed is that if the website contents are in certain language, the "title" of the page would likely to contain the language.
I'm not fluent in regular expression in any level, but since I had class about it last week, I thought using range match will be a good idea. As [a-z], [가-힣] will contain all the possible combination of letter with Korean alphabet.
It was successful to collect the ones that contained Korean letters, but I kept on failing filtering out them. From 2/11 to 3/5, I visited 726 webpages that presents Korean contents. There are total 4776, so brief way to exclude Korean letters will be 4776-726 = 4050 pages. However, regarding the small number of pages that present neither Korean nor English contents, I'd like to filter them out properly.
On another hand, for some reason, the Chrome extension I was using to track IP information stopped working. I personally emailed the developer to ask if it's finishing its service or having a temporary problem. It seemed to be having some issue, but didn't say it will permanently close the extension - so hopefully it will be back to service.
Develop a method to hack one (or more) of your tracking apps. Write a short reflection about your hack - how did you do it? What information is gained or lost? What are the implications of hacking your data in the way that you did?
So far I've been using both Reporter Application and Chrome Extensions along with Chrome History, however, for this week's activity using Chrome Extension seemed to be a suitable target. Although Reporter Application also tracks various data such as distance and temperature, because it's "reporting" system - I can always refuse to submit my report.
The Chrome site tracking happens all the time, but in order to have the history in json format, I'm weekly using another extension called History export. There's another way to download the history as csv format. For my convenience, I use the extension. However, the extension does not include IP location so I have to manually type in the information.
The best way to obfuscate the Chrome history tracking is simple: usage of incognito window Under incognito, it's possible to avoid the auto-tracking of my website visits - therefore, those won't be exported to json file at the end of the week. I've actually been using this method when I revisit some websites in order to check their IP locations; because as I mentioned above, they don't automatically get saved and exported. All the extensions are off in incognito window as default, so it's important to allow access of IP Tracking Extension.
Design or prototype an intervention that would help you to change your behavior based on the data you've gathered or based on the service you designed in you Quant Self Service. Tech or community or social based interventions are fair game.
The following application only focuses on writing thorough keyboard in either mobile device or pc. If you are a new user, it will ask the access to data about when you change your language, because it can be sensitive information. Once the user confirms, it lands to the Welcome (Get Started) page and will set up language types and devices to synchronize.
After the registration, the application won't ask accessibility question unless the user desires to stop the process of collecting data. Instead of Welcome page, now it will directly land on profile page and shows the average usage of different languages, list of languages, and list of synchronized devices. This page also has a role as setting page, so any visual change, language and device reset can be done in here as well. In order to see more details about data, tap the left top button and it will land on Time Map page. The default view of Time Map page is daily based.
Once in the Time Map page, the user can navigate to further information as weekly based, monthly based, or yearly based data. Each page's graphic is color-coded according to language, which is adjustable element in setting page. Through these Time Map sections, the user can discover such aspects like: "I use more Korean during weekends", "English is my main language while I'm not on vacation", and "My usage of English is increasing every year".
Develop a mini service concept around your own personal data.
Using "dear data" as a guide, create a set of rules to visualize your data - you may use digital tools, but analog style is encouraged. Think about the ways in which Georgia and Stefanie parameterized the aspects of their records to produce their visualizations. Find ways to express your own personal style and aesthetic in the implementation of your rules.
My initial discussion about Dear Data in class was done with Krizia and Miki, and we decided to do a project about a daily commute (an in-class sketch is included on the first image). Unfortunately, we struggled to adjust our schedule for further meeting, so the collective visualization that adds all our data was canceled. Nevertheless, I proceeded my personal one and was surprised that my visualization is very different from Miki's work, despite of the same topic.
This is the backside of my project, and as it's mentioned: one dot represents one minute. I found out that I have cycle of "walking - waiting train - riding train - walking" every time I commute, so I distinguished each part with different color. Color for "walking" changes upon weather, although if it happens during night~midnight it will be consistently dark navy.
When I collected data, I didn't want to carry around several pens and impulsively make mistakes on Joey's awesome paper. To avoid that, I made a little form in flash cards so I can quickly write down times. The data for February 9th is bit extraordinary, because I went home late after drinking for while. Surprisingly, I kept myself to continuously write down data but in extra messy way. Not to mention the different distance changed the overall commute time in much longer way and I ran out of space in the final piece only for the day.
Document your methodology for answering the questions you've set out last week - what are the tools you're using, the frequency of your measurements, helpful how-tos, pain-points and how you've overcome them, etc. Include photos, illustrations, charts, graphics, gifs, or video if necessary to effectively communicate and document your process.
Find 3-5 examples of projects that relate to self-tracking and the quantified self and write a 1. short summary description of the project, 2. the project's broader significance, and 3. why it is interesting to you. When possible, speak to the project implementation as a way to catalog useful methodologies.
Write a short reflection about what your current relationship with self-tracking (e.g. hopes, dreams, perceptions), questions you have about self-tracking and how it could help or harm you, and how you hope the course will help facilitate your interests. Write about which questions you've identified to track, how you plan to track those variables of interest, and what challenges you expect to encounter as well as what you hope to learn.
When I hear about self-tracking, it immediately reminds me of a class I took during my undergraduate year, called Relational Design. It was a class focus on collecting massive amount of data from survey, documentation, and archive and transforming it into a meaningful graphic design form. One project that is specifically about self-tracking is the untitled project I took photos of every meal I ate.
It was fun as much as it was bothering, and made me realize certain diet patterns I wasn't aware of. However, it wasn't the most interesting projects I've done - and it's proven by the fact that I have no proper documentation of it. When I took photos of the food I ate, it didn't only contain information about ingredients. Those images contained all different sorts of information such as brands, location/background, and time/brightness. Also, I wasn't quite clear what can be "meal" to me, while I'm the type of person who eats heavy snacks quite often. The project taught me that solid rules and restrictions of collecting data, will give more regular and simpler outcome - which is easier to pull pattern out of it. For example, if I only collected the geographical sources of ingredients - it might have created a much meaningful project. On another hand, the action of collecting data will be harder, because not all types of food have clear origins of ingredients (or there can be "unknown" category).
Sometimes, that's not what people always want from archiving and documentation. Archive without rules is exciting as well, and I love all my meaningless photos and Instagram posts. The part that majority of people feel creepy about is that even from those meaningless photo uploads and clicks, companies are still available to quantify something from you. Maybe every component about myself can be quantified, and I just don't have enough tools to do so. As I've mentioned in my previous project, my goal for the next self-tracking is being less arbitrary as much as possible, while keeping interesting topic to track. Ultimately, I hope I learn something unknown about myself through this tracking.