Dig 101 Final Project

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Angle 1: The Artifact Itself

With the advent of radio people were able to enjoy oral content from all over the place. Broadcasters could transmit music, news, or conversations over the airwaves and as radio evolved listeners could tune in from the comfort of their own home or during a road trip in the car. As technology has evolved so has our broadcasting. The newest and most popular form of broadcast media is podcasting. Podcasting leverages many of the advancement and benefits of modern technology. Podcasts, defined by Webster’s Dictionary as “a music or talk program made available for digital download,” came into existence around the early 2000s. Alongside the development of the iPhone, the term podcast was dubbed by BBC journalist Ben Hamersley combining the two terms “broadcast” and “iPhone”. Over the past decade podcasts have become more and more prevalent, especially among young people, with 42% of people aged 18-34 being weekly podcast listeners. Apple was the first major company to integrate podcasts into their general interface, establishing iTunes as the premier destination for pods. Culture critic Nicholas Quah identifies three distinct inflection points. With iTunes’s establishment of a legitimate platform being the first, Quah then points to the introduction of the iPhone 3G. This new device allowed users to download audio files remotely bolstering podcasts stock among “on-the-go” users. This mobility that podcasts provide is a crucial aspect of the medium. In his article “The mp3 as a Cultural Artifact” Jonathon Stern presents the concept of a “container technology”. He argues the mp3 is not a vital artifact in and of itself but that the crux of its utility lies within the content that it contains. Continuing he describes the novelty of these containers as lying in their mobility and compression. Users are able to use, share, and modify the content across a myriad of platforms at great speed and efficiency. Additionally, the files are small enough to allow users to download and delete them in large quantities. Podcasts can be understood from a similar perspective and reflect many of the same benefits. Steve Jobs described podcasts as “Tivo for Radio” and this characterization highlights the essential attributes of podcasts. They can be easily accessed at any time and user can select which content they want to view. Stern continues his point writing, “They take up less space than other kinds of digital recordings and when they are listened to, they are experienced as music, not as file format.” For many podcast users, their experience is similar. Podcasts have become a source for news, politics, tutorials, and all kinds of various media. Consequently, users associate each podcast with the content it contains. One might say “I’m listening to the news” while listening to a BBC podcast on the latest events as opposed to “I’m listening to a news podcast”. Most podcasts are available for free download and podcast publishers rely primarily on advertising revenue to sustain them. Thee revenues have increased dramatically in the very recent past. According to a case study by IAB podcast revenues in 2015 totaled 69 million dollars. By 2016 these figures had risen to 119 million and are projected to reach 220 million in 2017.in the past week Apple has released its beta version of advertisement analytics on podcasts. This information will provide podcast creators and advertising company more detailed information on who is listening and to what extent. While previously creators could access only the total number of downloads these new analytics will show how many downloaded podcasts actually get listened to, exactly how long they are listened to and perhaps most importantly whether or not listeners fast forward through advertisements. This new information could spurn additional investment on the part of advertisers but could also show these ads to be ineffective.

Apple’s new analytics platform


Angle 2: Cultural Representation

The resurgence of podcasts is a relatively recent phenomenon and thus their presence in popular media is limited. But the kids television show ICarly serves as an instance of cultural representation. The first episode of iCarly premiered on September 8, 2007 and the show lasted until November 23, 2012. The show centers around Carly Shay, a teenager living with her older brother in Los Angeles, and her two friends Sam Puckett and Freddie Benson. The premise of the show starts with Freddie, unbeknownst to them, recording Carly and Sam during a school talent show. Freddie, a tech wizard, posts the video online. The recording generates a wide viewership and the web audience gravitates towards Carly and Sam’s chemistry and humorous personas. Inspired by the reception the trio begin to produce regular episodes of their new web show, iCarly. Their web show features a wide range of mostly silly content, including talent contests, cooking tutorials, and famously (at least to fans of the show) random dancing. While the webcast obviously differs from the podcast, in that it features a visual aspect, it still bears many similarities to the podcast and iCarly highlights what would become some of the most important qualities of the podcast. The internet in general has increased the access of the public to a wide array of content but has also reduced the barriers to creating content and given a platform to produce content for almost anyone who desires to do so. Without home internet or even a computer people can still access the internet and all the content housed there with just a smartphone and at least theoretically create a podcast using only those same tools. The iCarly show created by a few teenagers with a webcam highlights this fact. Another interesting aspect of the iCarly show was the element of fan interaction. Bill Bradley, in his article 11 Things You Didn’t Know about iCarly, describes the process of fan interaction on the show. The iCarly website featured a section where views could submit commentary and the show would often feature videos submitted by real fans of the show doing similar activities to the ones featured on the fictional web show. The show also contained Carly and Sam’s reaction to the fan videos as part of the webcast. This aspect allowed viewers to feel connected to the characters and made them feel part of a collective community. Users were able to submit not only videos on themselves but also general feedback, which the writers and actors would often incorporate into the show. This stands in stark contrast to most traditional TV shows where viewers watch their favorite show and then wait for the next episode. This aspect of iCarly also highlights the openness and interactivity of the show and foreshadowed the way in which podcasts would operate. Podcasts also commonly feature interactions with the audience. With over 200,00 different podcasts on iTunes, each podcast has its own audience some more specific than others. This creation of communities establishes an intimate network. Consumers leave reviews which create more visibility in the public sphere and in terms of the algorithms on iTunes and other platforms that promote popular and widely discussed pods.

Angle 3: History

Podcasts have an interesting hand varied history. They are at their core broadcast media with a repurposed format. They can be traced back originally to radio broadcasts where personalities would present music or talk shows as entertainment for the home. As technology progressed radio become more portable with Walkman, car radios, and other mobile devices. But with governmental control over radio waves and only established entities having access, a significant barrier to entry presented itself and thus the people who could produce radio content were severely limited. They were limited in how they could listen, who they could listen to and when they could listen. The development of the web saw the advent of internet radio an important precursor to podcasts. The internet provided a centralized location for the aggregation of content. But the aggregated, subscription based model that also allowed downloads did not take shape until the early 2000s. The first device of this kind was i2Go. Originally priced at 500 dollars, the i2Go allowed users to automatically download episodic content from a companion website that featured programs on news and entertainment as well as music. While it was not particularly portable the advent of automatic downloads was groundbreaking and set the stage for podcasts. The project was short lived and i2Go folded during the dot-com crash.

2000 i2Go

Around 2000 two software developers, Dave Winer and Adam Curry theorized about solving the problems with delivering catered and downloadable content to users seamlessly as Todd Cochrane details in his book Podcasting: Do It Yourself Guide. They aimed to create a mechanism to download audio files from their favorite websites for later listening. They turned to RSS (Real Simple Syndication) as a springboard. Curry and Winer proposed using enclosures, or embedded content in RSS feeds to circumvent issues of bandwidth. Using basic software users could “catch” files embedded in these feeds automatically. Winer wrote a script that would then take these files and place them in a centralized location like an iTunes library. Users now had a way to efficiently download and aggregate content. This step, while seemingly innocuous was crucial for the implementation of podcasts distributed to the masses. Everyday user would likely be unable to program scripts or complete a multi-step process with multiple platforms. The automation and integration with a centralized library was critical to making the content easily accessible. Winer created a RSS feed for a colleague’s weblog that included enclosures. The weblog contained interviews with various political figures, and personalities. After accumulating enough interviews Winer released them as enclosures within the RSS feed. This was the first official podcast and the idea spurred on software engineers to improve upon the concept. As others borrowed from Winer and Curry the number of podcasts grew and radio shows began integrating internet access in their programming. While the technical workings of podcasting still seemed complex the relative costs of producing podcasts grew the number of content creators. The introduction of Apple into the podcasting market saw a huge rise in visibility of the medium. Apple, providing sleek and streamlined platform to consumers spurned a rise in everyday consumers removing podcasts from their previously specialized RSS arena. As the number of existing podcasts rose, so did the number of aggregators. Alternate platforms like PodcastAlley and The Podcast Network also housed countless programs and like Apple allowed users to search and discover new content. These added features and accessibility significantly grew the medium and set it up for the widespread success it enjoys today.


Works Cited


Perez, Sarah. “Apple launches its podcast analytics service into beta.” TechCrunch, TechCrunch, 14 Dec. 2017, techcrunch.com/2017/12/14/apple-launches-its-podcast-analytics-service-into-beta/.

Quah, Nicholas. “The Three Fundamental Moments of Podcasts’ Crazy Rise.” Wired, Conde Nast, 4 Oct. 2017, www.wired.com/story/podcast-three-watershed-moments/.

Stern, Jonathon . “The mp3 as Cultural Artifact.” New Media and Society, vol. 8, no. 5, 1 Oct. 2006.


Bradley, Bill. “11 Things You Didn’t Know About ‘iCarly’.” The Huffington Post, TheHuffingtonPost.com, 23 Nov. 2014, www.huffingtonpost.com/2014/11/23/icarly-trivia-facts_n_6196682.html.


Cochrane, Todd. “History of podcasting.” Blubrry Podcasting – Podcast Hosting, Statistics, WordPress Hosting, Syndication Tools and Directory, create.blubrry.com/manual/about-podcasting/history-of-podcasting-new/.

Doyle, Bob. “The First Podcast.” EContent Magazine, 7 Sept. 2005, www.econtentmag.com/Articles/ArticleReader.aspx?ArticleID=13515.


Posted from DIG 101 by Ellis C

Lab 7: Image Analysis – Get Out

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lmj analysis

For my image analysis, I chose the 2017 smash hit Get Out. One of the striking things I observed well watching this movie is the subtle tonal shifts in the art direction of the film. The work is supposed to appear familiar and relatable, a regular guy goes home with a regular girl to meet her parents. However, beneath this normalcy the screenwriter and director use shifts in color and subtle tone to make the audience feel uneasy. These patterns of tonal shifts are visible in all three of the presented images. In the barcode, we see a darker, meaner palette of color followed by more light and a seemingly “regular” assortment of colors. Additionally, in the plot image, we see that the lighter, brighter color palette comprises a much larger number of shots than those shot with a dark array of color. This makes a lot of sense because of the director’s efforts to create unease and tension among members of the audience. Many of my friends called Get Out one of the most unnerving movie-going experiences of their lifetime. This creepy experience is definitely aided by the sparse and intentional use of color, helping blur the lines between the normal and abnormal, and what is theatrical dramatization and what is a reflection of reality. This interpretation of the use of color and tone in Get Out is also visible in the montage, as we see shifts from shots of dark interiors to bright shots of the outdoors. The montage image is particularly helpful because it lets us consider the color palette of the film and observe trends on a macro scale while allowing us to root our interpretation firmly in the actual content of the movie by detailing particular scenes. Due to the unique evident quality of this image, I believe it to be the most valuable of the three. However, by being able to explain all of them and put them in conversation with one another, I believe I was able to achieve a more comprehensive analysis than I would have been able to with solely the montage.

Ultimately, if I had more time to do movie analysis I would really like the look at the trends in color and light usage in thrillers. Horror movies usually take a sledgehammer approach to unnerving their audience. Meanwhile, thrillers have to be subtle with how they mess with their audience. Were I to do a large scale image analysis of the stills parsed from other thrillers, I believe I would see a similar trend of dark shots being sparsely deployed and frequently contrasted with long stretches of bright, light palette shots in order to subtlely evoke a feeling of unease within the viewer.

Posted from My blog by Will H.

The Dangers of Algorithms

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In his article The 10 Algorithms that Dominate Our Lives George Dvorsky details the numerous avenues in which algorithms dominate our everyday lives. Whether it be using from using a google search or seeing targeted advertisements on Facebook these computerized instructions permeate almost all aspects of our digital lives. While these algorithms are usually helpful Dvorsky draws attention to one application of algorithms that seems to have dangerous potential.  Recently these algorithms have infiltrated the financials sphere and are being utilized to execute what is referred to as high frequency stock trading.

And while this raises the usual ethical concerns around the replacement of human labor with automation, the dangers of automatic financial actions are more serious. Relative to humans these algorithms operate at hyperspeed and thus the sheer number of transactions is exponentially increased. Unchecked they can form a predator-prey ecosystem that can result in a downward spiral. In 2010 this culminated in a “micro-crash” where the market fell 1000 points in a matter of minutes before quickly rising again. These malfunctions are more or less harmless when talking about algorithms that fail to censor an offensive comment or an advertisement for something we would never buy but when dealing with finance the consequences are graver. These financial instruments are tied to real world assets that determine people’s livelihood. Mistakes could cost a pension or a savings fund. While there are undoubtedly countless realms where the efficiency and processing power of algorithms are invaluable and improve user experience, lack of regulation around novel financial instruments has put our country in hot water in the very recent past. I feel we should take caution in applying them to the most sensitive aspects of our lives where the risks are far greater.


Works Consulted




Posted from DIG 101 by Ellis C

Issues of Privacy with Ad Algorithms

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Have you ever been confused, when you are looking at webpage that has an advertising side bar, and something that you often look up is popping up as the ad? Personally, this always kind of freaked me out; how did this specific site know that I had looked this up in the past? Could other sites, and to go further, people, know that this is what I was looking up?

After reading George Dvorksy’s article, this phenomenon made a little more sense to me. He mentioned two algorithms, “You May Also Enjoy…” in which certain sites like Amazon and Netflix suggest things the user might like based on things they have previously bought or watched, and “Google AdWords” in which an algorithm takes key words or behavior online to suggest “contextual advertising.” These algorithms are exactly what I think of when I see ads pop up on websites that are for a website that I had previously browsed. For example, the below picture is a capture of a Spanish translating site I use. The advertisement on the side is for Anthropologie, a clothing company that I often visit online to browse for clothes.

This image is a capture of an internet page from my personal computer. 

So an algorithm is processing my commonly-visited sites and searches and producing a visual image for an advertisement of what it has decided, based on its data of my searches, is something that I would like to see.

I can see how this can be seen as beneficial, but I also find it to be somewhat of an invasion of privacy by an algorithm. Not that most of us have much to hide, but personal browsing is what it sounds like- personal. And yet a computer program is able to take what we look up on our private computers and reproduce that to us. And I think that is the scariest part- that it isn’t even a human doing this, but a computer. A computer algorithm can immediately have access to our internet searches and visited websites. For me, that puts into question (similar to questions of Artificial Intelligence), what else can a computer do? How much power do they really have?

Posted from Digital Studies 101 Blog by Lindsay

Why I love .FLACs

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In the article assigned, The 10 Algorithms that Dominate Our World, #8 was MP3 compression. Initially, I thought that the more general category of data compression would be more appropriate as shrinking files of all types – from pdfs to psds – is incredibly important in the dissemination of data among users. We discussed in class the mp3 being described by an author as “promiscuous.” Part of what enabled the popularity of the file structure was its relatively tiny size. This enabled sharing as well as compatibility across a litany of devices. Similarly, services like Netflix and Hulu would be impossible without modern video bit rate reduction techniques. Data compression also allows us to spend relatively little time buffering and more time binging. And while we’re on the topic of video, its own digital proliferation can also be attributed to compression. Videos are everpresent nowadays whether it’s on our phones, laptops, or smart fridges. This is also thanks to techniques that convert these video files into universally readable formats which are also in file sizes previously thought impossible relatively recently.

Also, in thinking about mp3 compression I think we should also take a moment to appreciate uncompressed music formats. I personally love .FLAC. The file size of an .flac is usually about 10 times the size of an mp3. It’s a totally uncompressed audio file format that is often referred to as ‘lossless’ audio. Another popular lossless format you may have heard of is m4a.


I don’t have my entire library in lossless format. 90% of the time and for about 98% of the music in my library, I don’t need to deeply and granularly appreciate the minutae of an artist’s work. But for a few albums, it’s really important for me to be able to sit down and take in everything the artist and producer intended with the recording. This is the type of specialized, intense listening that lossless file formats enable.

Posted from My blog by Will H.

Is Google getting less racist? Or less controversial?

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In Safiya Umoja Noble’s essay, “Google Search: Hyper-visibility as a Means of Rendering Black Women and Girls Invisible”, it was shocking to see the racist and misogynistic links appear when one searched “Black girls” in 2011. What was more surprising is how vastly different Google searches work within the span of just six years.

Fig. 1
Fig. 2

Fig. 1 above shows the searched links included in Noble’s essay, while Fig. 2 shows the searched links today in 2017. An immediate difference is that there actually no pornographic links or sites that display black women as a fetish. In fact, there are no major links within the first several pages of the Google search. Instead, we get a much more prominent focus on cultural identity, social issues, and celebration of identity. However, a quick search for “Hispanic girls” and “Asian girls” did not yield the same results. Within the first page… and second… and third, there were various links to pornographic or semi-pornographic sites that collectively objectifies the women. Whether it be inherently lewd (Found on first page) or under the guise of appreciation, Google has very obviously not become non-racist or non-sexist.

In comparison to searches for black women, there is a distinct lack of sensitivity towards other minorities (I conducted the same searches for “Middle Eastern girls” and ethnicities such as “Japanese girls” which yielded the same results). This raises the question: Has Google and algorithms in general on the internet gotten less racist over time? Or simply less controversial? In the context of growing racial tensions and the vocal Black Lives Matter movement, it appears that many sites are taking a step back on more hotly debated issues in order to protect their image instead of directly addressing them. The so-called “model minority asians” are still being underrepresented in all the right categories and overrepresented in all the wrong ones. Hispanic people still face discrimination and racism under the Trump administration, yet the internet continues to sexualize hispanic women. It is obvious that the internet, or rather the users behind it, are trying to stop appearing racist, rather than actually stop being racist.


Posted from our fascination by Tony N.

Are Dating Sites Lying To You?

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Reading George Dvorsky’s, The 10 Algorithms That Dominate Our World” (2014), got me thinking if the algorithms used in dating sites really work. After a while of browsing different articles online, I was quite shocked to find out that most websites were heavily disagreeing with the fact that these couple-matching algorithms actually work.

From Giphy

According to an article by The Huffington Port, “dating site algorithms are meaningless. They really don’t do anything.” From a Northwestern University research published in 2012, these matching algorithms have proven to be only insignificantly better at matching people than those same people are being matched by random chance.

These algorithms are not necessarily successful because at the end of the day relationships stand on much more than just the color of one’s eyes or the fact that he or she may or may not have a college degree. A computer algorithm cannot figure out if your character matches with someone’s else’s, or if you hit it off with that person on your first day because those are things that can easily be affected by many other factors such as the place you chose to go out  to on your first date, the mood the other person happens to be in on that day, their smile, their smell, etc., etc.

Even OKCupid’s ability to rate the importance of the data has been questioned by many, in regards to the fact that people can easily get away with either “lying” or just by the simple fact that we are usually bad in rating our own preferences when it comes to relationships. It is therefore unlikely that these date-matching-algorithms based upon simple data collected question will be sufficient enough to identify one’s right long-term partner.

Posted from DIG101 by Danae

Real Information or an Ad?

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In Safiya Umoja Noble’s article, “Google Search: Hyper-visibility as a Means of Rendering Black Women and Girls Invisible,” she explores the results Google provides when using “Black girls” and what this means in a historical and social context. I found Noble’s point about the distinction between real information and advertising to be particularly compelling. I recently went through an interview process with a company who aims to maximize clicks on their client’s paid ads as well as natural searches. Until learning about this process, I had no idea how search engines’ results were ordered.

The ability for companies to pay for their website to appear higher within the search results acts to bias the internet. This can be problematic, particularly for Black women as Noble pointed out or minorities more generally, as it acts to reinforce and strength the dominant political or social groups stance. The Dove commercial we saw last week in class is a prime example of this issue. If this ad was one that the company choose to pay more for it to appear higher on the search results, by nature more people would see it. This means that not only are the groups Noble mentions “highly sexualized and even stigmatized” when they are searched for directly, the normalization of racist or misogynist search results more broadly reinforces hegemonic narratives.


The financial aspect of search engines allows the engine itself to “reflect and re-instantiate the current social climate and prevailing social and cultural values.” Moreover, this major influence in how results appears adds to the cyclical nature of online racial disparities. Google, like many other search engines, denies responsibility for search results despite the fact they are not random or based upon popularity alone. However, studies such as the case of the Google searches conducted in 2011 illustrates that this is an issue of the digital age that needs to be addressed.

Posted from Intro to Digital Studies by Kat

NSA Data Collection

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Source linked here.

As technology has advanced substantially over the years, government agencies have utilized these advances to collect and analyze data that has been collected. The NSA more specifically has developed countless algorithms to collect, sort and analyze data on the citizens of the United States. No longer is surveillance done predominantly by people, but it is done by computers and algorithms that have been specifically programmed for surveillance. This includes listening to phone calls, facial recognition, collection of a person’s writing online, texts, emails and countless other forms of information. According to George Dvorksy in his article “The 10 Algorithms That Dominate Our World”, algorithms are used to monitor people’s information now because “there is far too much data for humans to collect and interpret.” This is astounding because what the author is saying here is that the NSA collects so much data on individual citizens that humans are simply incapable of not only being able to collect the data but also interpret it.

Source linked here.

Now, controversy has erupted surrounding what exactly the NSA collects from private citizens and does not consider an invasion of privacy. The NSA simply does not believe that they are collecting our data and that the only data that is considered “collected” is what has been read by a human, not a computer running an algorithm. Essentially the NSA has unlimited access to the information of citizens as long as no one admits to having seen the data that the computers have collected. Scary thought. The clause that defines what it means to be “collected” in relation to data was written in 1982…Maybe it’s time for the NSA to update their data collection policies for the modern era.






Posted from My blog by Charlie

Google Black Girls Now

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Before I start talking, take a look at this google search taken from the article “Google Search: Hyper-Visibility as a Means of Rendering Black Women and Girls Invisible”.

Using key words “Black girls,” google search provides these top choices.

Wow. I mean I’m shocked. I never had to do a google search like this, but you can just tell from this picture that Black women are sexualized and used as a marketing tactic by the porn industry. Do we blame the porn industry for being smart and tackling these fetishes of men who surf pornographic sites? They do their job well, but in turn, perpetuate the sexualized and objectified view of Black women on the web. Like the reading said, these views of Black women as “sexually insatiable and gratuitous,” are rooted in slavery and how masters took advantage of these women being considered property and therefore, could not be victims of rape.

Google has a large influence as they’re viewed as somewhat not needing to commercialize/market/advertise companies on their search queries. This leads to people believing that the top search results are popular and reflects everyone’s interests — which they may, I can’t agree or refute anything. This was my thinking. However, I do think these results reflect society at that time, but things have changed, and when you google “Black girls,” there are no sexualized results, but rather, are more empowering results. A great movement towards black girl positivity.

Posted from Digital 101 by Christy