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MIT 1700 Midterm Review.pdf

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Psychology 1000

MIT 1700: Midterm Review February 20, 2014 Raw Data: · Lisa Gitelman (author) describes raw data as an oxymoron (a term defining two terms as contradictory. Juxtaposing). It is her firm belief that data is anything but “raw”, that we shouldn’t think of data as a natural resource but as a cultural one that needs to be generated, protected, and interpreted. ▯ Data Mining: · The computational process of discovering patterns in large data sets. This can be deemed extremely valuable, lending society the opportunity to not only collect data, but to begin the rigorous process of understanding it. · Quote: “If the imperative of data mining is to continue to gather more data about everything, its promise is to put this data to work, not necessarily to make sense of it. Indeed the goal of both data mining and predictive analytics is to generate useful patterns that are far beyond the ability of the human mind to detect or even explain.” · Example: If we could track the social media usage of the Tsarnaev brothers (i.e. YouTube, Facebook, Twitter, etc), it may have led us the possibility of preventing the Boston bombings. With data mining, we would have been able to understand the threat these two brothers pose and take the necessary steps to prevent the incident from ever occurring. ▯ Metadata: · Definition: A set of data used to describe and interrelate other sets of data. · It is important to not only be able to “collect” the continuous streams of data, but to “understand” and “process” it as well. The concept of metadata presents the opportune moment for an individual to understand the information in front of them and deem its value accordingly (we will no longer be subject to an information overload). ▯ Big Data: • Definition: It can be argued that big data is the commitment of looking at data in term of qualitative rather than quantitative. • Quote: “For example, we start with 10x10 pixel image (100 pixels in total), and resize it to 1000x1000 (one million pixels in total). We do not get any new details – only larger pixels. This is exactly what happens when you use a small sample to predict the behavior of a much larger population. A ‘pixel’ that originally represented MIT 1700: Midterm Review February 20, 2014 on person comes to represent 1000 people who all assume to behave in exactly the same way.” • Explanation: The concept of big data can be interpreted in two ways. The first is literal, outlining the amount of information we have available to us. This can be deemed as a positive but a majority of the time, carries negative repercussions. It is not important to have available an abundance of information, but only the important details. This is closely tied to the idea of seeking out quality over quantity, better pieces of information rather than more pieces of information. ▯ Distributed Networks: · Definition: A specific network architecture characterized by equity between nodes, bi-directional links, a high degree of redundancy and general lack of internal hierarchy. · Quote: “The distributed network creates new, robust structures for organization and control; they do not remove organization and control (interactivity).” · Explanation: It is free floating control that are inherent in distributed networks, the ability to move the information seamlessly through different platforms without the reliance of an overseeing entity (centralized state). ARPAnet is a key example of the distributed network (packet-switching system). ▯ Protocol: · Definition: This can refer to the technology of organization and control operating in distributed networks. It functions largely without relying on hierarchical, pyramidal, or centralized mechanisms; it is flat and smooth; it is universal, flexible and robust. ▯ Inverse Panopticon: · Definition: When you know you have been watched but you act as if you are not (the rebelling towards surveillance). ▯ Software as Ideology (Interface Effect): · Wendy Chun argues that software can be deemed a functional analog (i.e. relating to or using signals or information represented by a continuously variable physical quantity such as spatial position or voltage) to an ideology (i.e. a system of ideas and ideals, esp. one that forms the basis of economic or political theory and policy). MIT 1700: Midterm Review February 20, 2014 · Explanation: The information we gather from software (or technology) is continuously present in our physical world, leading us to develop the ideologies and progress as a society together. · Quote: Althusser argues, “All ideology hails of interpellants (the process of activating us).” o He emphasizes how the situation always precedes the subject. Individual subjects are presented principally as produced by social forces, rather than acting as powerful independent agents with self-produced identities. ▯ Dataveillance: · Definition: Is the systematic use of personal data systems in the investigation or monitoring of the actions or communications one or more persons. · An individual can be monitored through actions such as: credit card purchases, mobile phone calls, and internet use (the combination of characteristic surveillance and reliance on available data). Digital Footprint: · Definition: The closed loop takes data from the open loop and provides this as a new data input. This new data determines what the user has reacted to, or how they have been influenced. The feedback then builds a digital footprint based on social data, and the controller of the social digital footprint data can determine whom and why people purchase and behave. · The digital footprint can also reference to our behavior online. The decisions we make are permanently etched into the virtual realm, leaving us with an inability to conceal some of the choices we have made. We leave a trail with every click and most importantly, paint ourselves a digital identity (our footprint). · You are suspicious if you do not leave tracks, but you are closely monitored if you do (no method of winning in the virtual). ▯ Wages For Facebook: · In an attempt to draw upon feminine discourse (1970’s Wages for Housework) to extend the discussion of unwaged labor to new forms of value creation and exploitation online. · The wage gives the impression of a fair deal ▯ cannot be exploitation if you are being fiscally assisted. · Quote: “We want to call work what is work so we can rediscover friendship.” o We cannot be using Facebook with our honest intentions (to socialize) with the idea of being exploited lingering in the MIT 1700: Midterm Review February 20, 2014 back of our minds (institutions are using the information we provide for marketing purposes and human studies). ▯ Platformativity: · Definition: By publishing information online, we are sharing our information with others. But, each experience can be deemed to happen on a different platform (we move from platform to platform to gain our knowledge of others). ▯ Digital Alienation: · Explanation: There is a “dual” character of networked activity: the conscious action and the captured information. Users have little choice over whether this data is generated and little say in how it is used: in this sense we might describe the generation and use of this data as the alienated or estranged dimension of their activity. · Important: Alienation occurs when our own activity appears as something turned back against us as, “alien power” (i.e. interactive markets take our actions and use it to develop ideas geared towards us). ▯ User-Generated Value: · The discovery of a free worker through the concept of “immaterial labor”. We are sharing with one another our own information and face the opportunity of expanding our personal knowledge through this open platform. ▯ ▯ Network: ▯ Online Advertising: Web Evolution E-Commerce Evolution OnlineAd Evolution Yesterday world: Get everyonee “Here is what we portals and displayc connected via the have”. advertising (e.g. Internet. display and search). Today Web 2.0 is about like- E-Commerce 2.0: OnlineAd 2.0: minded people: Share “People who bought Dynamic ad and interact with this, also bought placement with others in the group. that!” contextual, behavioral, demographic and geographic targeting. MIT 1700: Midterm Review February 20, 2014 Tomorrow Web 3.0 is about the E-Commerce 3.0: OnlineAd 3.0: individual: Receive “We believe this is Personalized ad the right content at what you are looking display based on user the right time from for.” preferences, anywhere. community and other characteristics. ▯ ▯ Web 1.0 (main characteristics): Information Centric · Text based, no commercials (read only content). · World Wide Web introduces graphic display. · Based on content delivery (information is more important than presentation). · Static (point A to point B). · Examples: Britannica Online,, content management system, etc. ▯ Web 2.0 (main characteristics): People Centric · Participation not publishing ▯ Open source movement ▯ People contributing, not only consuming. · User generated content ▯ Cheap web development. · Services not product ▯ Push to viral marketing. · Lots of face content/Interactive user experience. · Architecture of participation. · Examples: Wikipedia, Napster, Wiki … (includes apps, blogging, mapping, tagging, searching, sharing, etc). ▯ Web 3.0 (main characteristics): Machine Centric · This will be about semantic web (the meaning of data), personalization, intelligent search and behavioral advertising. · It can be tailored to the user, no longer leaving many decisions for the said individual to make. E-Business (Examples): · A lot of businesses began a growing interest and dedication to the Internet (E-Business). · This innovative approach was growing far too fast, leading to a failure to develop a clear economic model. Hence, there is no effective organization of the e-advertising. · Example: Amazon shares started on May 15, 1997 at $18/share, rising to more than $100 and subsequently dropping to less than $10. o The big companies managed to survive the crash. MIT 1700: Midterm Review February 20, 2014 · Important: A new wave of companies immerged after the crash. These are: social networks, music/media download and search engines (progressive methods of the E-Business through personal marketing and direct consumer purchases). ▯ Dot-Com Bubble: · The dot-com bubble (also referred to as the dot-com boom, the Internet bubble and the information technology bubble) was a historic speculative bubble covering roughly 1997-2000 during which stock markets in industrialized nations saw their equity value rise rapidly from growth in the Internet sector and related fields. ▯ Over Connectedness: · It can be defined as a part of the information diet, a unfortunate repercussion of our ever developing culture. · We are over connected toe everyone due to social media treating it as a job (making it impossible to sustain genuine human connections). ▯ Information as Need: ▯ Information as Environment: Cyborgs: Organic + Mechanical. “cybernetic organisms” Inforg: human beings understood as information entities. Freudian Robot: Any networked being that embodies the feedback loop of human-machine simulacra and cannot free her/himself from the network Ubiquitous can be defined as "existing or being everywhere at the same time," "constantly encountered," and "widespread." When applying this concept to technology, the term ubiquitous implies that technology is everywhere and we use it all the time. Because of the pervasiveness of these technologies, we tend to use them without thinking about th
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