Algorithms in Interactive Media

This week we learned about search engines and algorithms used in online media. Search engines, such as Google and Bing, are software systems designed to search for information on the World Wide Web. Results are displayed on SERPs, or Search Engine Results Pages. Their purpose is to provide the best results based upon specified search queries and keywords.

The three steps a search engine takes to provide users with what they require are:
Step One: Crawling - collecting data from the Internet and websites on the World Wide Web. about 0.5 billion websites are used for crawling in order to collect data for search engine results. A site must be public and linked in order to be a part of the crawling process.
Step Two: Indexing - sorting and categorizing collected data and storing it in a database. The collected data by the crawler is passed on to the indexer. It analyzes and sorts the data into various categories. Once a user enters their search query or keywords into the engine, it tries to match it with already indexed data sets.
Step Three: Processing Search Keyword - providing the best result from the database. This is where the algorithms come in. It filters by search engine system. Google, Bing, Yahoo, etc all use different algorithms. Search engine websites update their algorithms quite often in order to make searches more relevant to what the user wants. For example, Google updates their algorithm 100 or more times per year.

We also learned more about these algorithms. An algorithm is a series of conditions. If something happens, you must respond with this action. It requires a lot of coding to make an algorithm, including the use of "if... then" statements. With multiple conditions, you get better algorithmic results. Items like Twitter's "trending topics," online recommended stories, top search results, and product recommendations are all brought to you by algorithms.

In the article "Can an Algorithm be Wrong?" we learn about Twitter's algorithms used in their "Top Trends" and how it can be controversial due to the fact that it was not displaying topics that were in fact popular and trending. After the Occupy Wall Street event, people were tweeting #occupywallstreet all over Twitter for days on end. However, it failed to show up on Twitter's "Top Trends" section, which, if their algorithm was correct, should have been there based on the number of tweets sent out with that "#" within the allotted time period. This proves that in the end, the one behind the computer screen at Twitter's headquarters gets the final say in what shows up on that trend list. We also learned about another example of this in class, where one student said that "Justin Bieber" had to be blocked from the trend list due to his continual popularity. It really makes you think about whether or not these algorithms are the best thing for you.

My questions for this week are can all algorithms be trusted? Should we believe the algorithms that are determined by your own decisions, or by other users? On search engines, they try and predict what you would like to search for based on previous searches. But on websites like Amazon or Youtube, you are recommended to buy a product or watch a view based on how much other users liked the product or video. Which of these algorithms are better? Is it unfair of companies such as Twitter to control their algorithms and adjust them accordingly without informing their users?

Copyright and Copyleft

This week in class we learned about Copyright and Copyleft. It was a lot of information to learn, but it was very interesting to learn about different copyright laws and how it affects different groups. Copyright laws will affect a music artist in a completely different way it will affect a consumer of music.

First, we learned about the FCC. They are the Federal Communications Commission, and they control and regulate content on television, internet, radio, and so on. They can cause some controversy because of what they censor out of shows and artist's songs. We also learned about digital conversion, and how it benefits everybody. With digital conversion, television channels can have multiple sub-channels (for example, channel 8 can have channel 8-1, 8-2, 8-3, and so on) which provides more television stations per channel. This allows the FCC to gain more money in order to sell more bandwidth, allows broadcasting and cable companies to sell more advertisements, and have more content to be in demand by television watchers.

Next we talked about intellectual property, which I found to be very interesting. Intellectual property is property that belongs to a certain individual that is not tangible. It refers to the creations of the mind; such as inventions, literary works, and symbols. It's crazy to think that we as individuals can own property that isn't even tangible. They are things we view, see, and discuss every day, and people own them. The two categories of intellectual property are Industrial Property and Copyright. Industrial property refers to inventions, patents, trademarks, industrial designs, and geographic indications of source. Copyrighted intellectual property consists of artistic and literary works, novels, poems, plays, films, music, drawings, paintings, photos, sculptures, and architectural designs.

Copyright was a big topic of discussion in this past week's class. Copyright helps original artists, musical artists, designers, and more protect their work from being stolen and used by others for profit. Without copyright, anybody could claim something as their own and take credit for it.

Life without copyright.

I definitely understand the need for Copyrighting material. It helps original creators of different works to protect what is rightfully theirs. If a musical artist makes a hit song, it's their song to make profit off of, not any other musical artist's. Having protection from tampering and re-producing material is definitely a good thing to have.

Many people have different views on Copyright, however. Mark Helprin believes that Copyright is what protects all material from belonging to the rightful owners. This material, which could be a product of years and years of work, shouldn't just be available to anyone. In the wrong hands, it could cost a lot of money. Helprin believes that elongated Copyright years (100+ as of today) will help to benefit any beneficiary during the original creator's lifetime. Lessig, however, has a different view when it comes to Copyrighting material. He believes that it is important for us to make new material out of original concepts. To use previously created material as inspiration for future designs. With digital technology rapidly advancing, Lessig believes that we will continuously make new and improved content from original ideas.

I can see where both Helprin and Lessig are coming from in their standpoints on Copyright. On one hand, we need copyright to protect original works. But if we are so protective of them, it limits new content that can be released in the times to come. What will happen if we run out of ideas? What can we do to balance the two opposing sides of Copyrighting material? These are the questions that arise from this week's discussion.

Technology and Behavior

This week in class, we talked about regulation and the social construction of technology. The three E's in regulation are Education, Enforcement, and Engineering. The market, laws, architecture, and norms are all factors that majorly impact the way we regulate things in our everyday life, as well as online. We also learned about technological drama, and how less and less human power is needed to control and regulate what we do. Back in the day, there used to be doormen that would stand outside of a hotel or other building's door and open it for incoming patrons. Nowadays, we use technology and have these automatic doors that have sense when people are near it and then open by themselves, eliminating a need for human interaction with this specific action that happens so very often in our lives. One more example is an elevator operator, who you would find within the elevator that would control the floors you go to. Nowadays, elevators are completely controlled by technology, and you push a button for the floor you would like to go to. With the social construction of technology, many people view objects or symbols differently than they once would years ago. With the # function that is so commonly used on Twitter, the original meaning of that symbol has quickly faded away. Before Twitter, the # symbol was referred to as a "number sign"or a "pound sign" when using it on the telephone. Nowadays, whenever someone sees the # symbol, more often than not they will refer to it as the "hashtag," which is Twitter's name for it.

There are many examples like the one above that prove how much technology impacts the way we behave or think about something. One way I think that technology impacts behavior is the fact that it makes us significantly less social in the real world. Now that there are so many different forms of communicating with technology, either by phone calls, text messages, or social networking, there is less human interaction in the real world. "Why communicate face to face when we can communicate instantly from behind our computer screens, without even having to go anywhere?" is probably a sad truth thought of by many individuals. Even when you do spend time with your friends, think about how much time everyone spends looking at their phones throughout the time spent together. The more technology grows, the less social we become in reality. The only way around that is to simply put down the technology and spend time with the people you know and love. Here is a great video about cell phones and social behavior:

Another way technology impacts behavior is the way we view things. Just like the # - Hashtag debacle, there are many other symbols which we interpret in a different way than we once did thanks to technology. Again, because of Twitter (and now Facebook, YouTube, and a few other sites), the @ symbol's meaning has drastically changed. Sure, we still use it for email purposes. An email address wouldn't be an email address without the "@" symbol before the domain website the email was sending from. But now many people view it as a way to "tag" people in an online post. It's pretty crazy how much our behavior can be impacted by technology, and it certainly makes me curious as to how much it will change our lives in the future as technology grows.

Recommender Systems

I was really interested in this week's readings on recommender systems and how they can affect users' opinions on specific products that a service has to offer. When using applications such as Netflix or Pandora, they will recommend movies, TV shows, or music that you may like based on your previous selections. These suggestions don't force you to choose them, they are simply suggestions, but they can help open a user's eyes to new content they have never heard of before. These recommender systems are formulated by specific algorithms in order to determine what each specific user may like. If I like watching comedy movies on Netflix, then the "suggested" section of my Netflix account will mostly be filled with other Comedy movies that I haven't yet watched on Netflix. Pandora's entire experience is based on recommendations and suggestions. When you choose an artist, or a band, or a specific song that you like, it creates a whole personalized radio station around that one choice and gives you a playlist of other songs related to that one.

These recommender systems aren't perfect. Maybe you don't like some of the suggestions that they give you. This is where Pandora's "skip" button comes in handy. Maybe you share a Netflix account (because almost everybody does) and the suggested movies and television shows are programs you would never even consider watching. There are a few flaws in these algorithms, but the majority of the time these recommender systems really help, and they've definitely been the reason behind some of my favorite features to watch on Netflix.

Some questions do arise from this week's information, however. As I just previously mentioned, there are some flaws with these recommender systems. What can companies like Netflix do to improve their "recommended for you" section of their application when dealing with shared accounts? Can Pandora recognize the songs you skip and go even further to make sure songs by that particular artist don't show up again on your playlist? How influential are the "thumbs up" and "thumbs down" buttons on Pandora? Do many users take advantage of the recommender systems offered by these companies, or are they something people simply ignore? Do ratings by other users really affect how many others interact with that specific product? These are just some of the questions that I thought of while reading through the recommender systems article for this week.

-Frank Hines