Discuss your personalized experiences on the web and how “good” the predictive methods are relative to your tastes and interests.

Final Project: Data becomes you

One of the many takeaways from this module is the idea that you are Big Data. Our every movement on the web leaves traces and patterns of who we are and our interaction with the various platforms can shape our behavior in
return.

This assignment will require that you collect, analyze and visualize your own behavioral data. The data collection and reflection process should draft a personal story told with data. When aggregated to classmates’ work, the project will
result in a social analysis garnered from these stories and supporting resources.

Project Premise

There are two web activities being tracked here: online shopping and movie/tv streaming. You are charged with creating a presentation on the collective findings of the tracked data as well as your individual data collection.

Each student is required to share their data and engage with the collective data set to develop a more macro (social) analysis of the select web activities.

You will produce statistics and data visualizations and integrate media and academic resources. The analysis should be focused on the larger implications of web experiences mediated by predictive systems, and how individual behaviors impact and are impacted by these.

Individual Work

Preparation:

 Download the Data becomes you Data Entry Template in Module 5.1

 Collect your personal data for two (2) weeks, 14 consecutive days

 Locate at least two (2) good media pieces that discuss quantitative aspects about your platform (this

will also serve as a resource for the team project)
Data:


Using the rules of level of measurement choose the appropriate statistics to
 Calculate at least eight (8) distinct statistics: 4 for the individual data and 4 for the classlevel data
 Ensure to combine variables, i.e. rate, frequency and time
 Create at least four (4) data visualizations

Areas to Explore and in preparation of Presentation:

 What you thought

o Personal web-based habits

 How much time do you assume you spend online, generally

 What do you usually do online

 Do you interact with others online

 What’s the content of your interactions like, generally

 What interests you about web behavior turning into data?

 Does it cause you concerns? What/Why?

 What you found out
o Discuss your individual data/findings

 Integrate the various calculated statistics

 Include data visualization examples (with own data)

 Reflect on these findings

 How do the patterns you identified relate to your
o Self-understanding
o Habits
o Relationships

Final Project: Data becomes you
o Ect.

Discuss your personalized experiences on the web and how “good” the predictive methods are relative to your tastes and interests

o Discuss class-level data/findings

 Integrate the various calculated statistics

 Include data visualization examples (with own data)

 Reflect on these findings

What you know understand

o Integrate the resources (media, articles, readings) into an analysis of the aggregated individual data for the larger social analysis

o Turn results into informed statements about the social and personal implications of the web activities explored and the general dynamic of data-driven web services and consumption

Presentation

 Introduce the platforms you tracked
 Report minimum ten (10) statistics in the presentation
o May be integrated as data visualizations
o Four (4) of these must come from resources
o Six (6) from the aggregated class data

 Six (6) data visualizations from the aggregated class data should be displayed in the presentation

o Data visualizations from resources may be included in addition to the required six

 Analysis:

o Synthesize information, analyses, critiques, and conclusions from the exercise above and resources to form a cohesive analysis of the web-activities

o Present the main points of the analysis as recorded narration accompanied by summary statements and bullet points

 These should be integrated with the statistics and visualizations

 The presentation should tell a social story about our relationship with the web

 The presentation should last 15-20 minutes, including the recorded narration
o Review presentation tips in Module 4.3