DTC Homework #9

“And lest we forget, text itself is an invention, a technology. We treat it, however, as a base-level given in thinking about the essence of a message or a piece of communication.” – Maria Popova

In this quote Maria Popova points out that in our ever-changing world of technology, we forget that the things we have grown so used to were once brand new. People hold literature on such higher standings than modern technology even though what they think to be superior was once something to be wary of. When thought of in this way Twitter should really be thought of as nothing less than any other form of writing. Just as writing once became an essential part of communication (letters, emails, texts, etc.) Twitter could very well be headed the same direction. Everyone learns how to write in school and they use those skills learned to develop ideas into larger pieces of texts like essays. However, now people aren’t spending the majority of their time reading long winded articles or even blog posts. Being able to condense information into 280 characters is a valuable skill to have. People get their news and entertainment from the same source now, and in the same format. It’s not crazy to think that eventually kids will be taught how to cram the most information into a tweet, or how to make a cohesive thread. Writing changes with the times, and as we continue to make new ways to communicate it will have to adapt. Plays used to be written to last all day and provide a longer entertainment, but now that we have books and movies and the internet, no one’s focus has to be on one thing for any longer than they want it to be. While new inventions continue to draw our attention thinner, the normalcy of writing changing all together seems like a plausible solution to keep people consuming information.

DTC 101: Anonymous Data

In terms of data privacy I probably have very bad browsing habits. I regularly use websites which use cookies and subscribe to emails and other offers from sites I frequent. I allow Google Chrome to save all of my passwords and information just to make giving my data to other companies more convenient for me. I guess I’m not particularly mindful of where my data is going just because nothing I do on my computer is so private that it would be a disaster if it were leaked. In order to market towards me companies would only need to look at my online purchases and frequently viewed items. It seems as if I do most of my shopping online now with all of the free 2 day shipping options and all of my buying habits are out in the open. It’s obvious to me now even that the ads I get on my browser are tailored towards me based off of my internet searches and browsing history. I can also see this being transferred to my social media account as now I am seeing adds tailored to what I would usually only see as banners. As bad as it is, I like having ads come up that I’m actually interested in as apposed to those I really would find it annoying to be in the way of my feed. Recently, I’ve even noticed that it’s not just my actions online that affect the ads being placed in front of me, but what I say as well. There have been too many times that ads have popped up for things that I specifically remember having conversations about, but would never be interested in buying.

Data Visualization Blog Post

https://www.reddit.com/r/dataisbeautiful/comments/9dhv4e/sankey_graph_of_my_phone_spam_problem_charted/

This example of data visualization is a network map arranged from broad sets of data down to more specific categories. In this map the data being represented is one persons phone calls over the course of one year. It starts with only two main categories after the initial number of total calls, spam and trusted, before it gets very specific, who the actual caller was. The thickness of the lines shows the frequency if the caller, and the lines are easy to differentiate due to their difference in color. From all of this information I was able to learn that the vast majority of this person’s phone calls were spam calls, most of those unidentified. It seemed to be particularly useful to use this type of data visualization because of the sheer number of factors contributing to the data set; it is all arranged well enough that it doesn’t become confusing to look at. This would be particularly useful for people easily susceptible to scams. By analyzing and recognizing trends for scam phone calls, those people can be informed of the attributes and nature of scammers. I also find interest in the fact that this person has called their repair shop more times than their sister.

https://www.reddit.com/r/dataisbeautiful/comments/9dj53m/oc_one_india_equal_in_love_indian_supreme_court/

The data visualization above could only be described as a word cloud. It depicts words used in high frequency in tweets after India’s Supreme Court ruled out the criminalization of homosexuality. The bigger the word, the more times it was used in tweets. The format of this data visualization is important to the message being conveyed. With words like “love,” “LGBT,” and “India” having the most space in the image, a lot of attention is first drawn to them. Even smaller words still carry only positive messages which shows the campaign of the data. Certainly there must have been some hateful comments that were excluded form this research, so not the entire picture is shown. Besides that though, I learned of apparent overwhelming support of India’s Supreme Court decision, and I was able to learn it very quickly. There wasn’t a lot if thought or analyzing that had to go into this in order to interpret the results of the collected data. It’s interesting as to why they picked so many words the be green. There doesn’t seem to be any sort of pattern to the coloring of words, yet the grouping of green draw the eye to those 6 or 7 right by each other.