Brief note on Recommended Approach to Filter Bubble report

I. Approach

Two approaches were proposed in tutorial groups for detecting and analysing a personal filter bubble:

1. Comparison with another person’s filter bubble, by concurrent searches on separate devices.
Some suggestions:
 Since the algorithm of Google News is more strongly based on personalisation than Google, a Google News search should be included.
 Google autocomplete? Facebook search? DuckDuckGo?
 Advertisements brought up in Google, on Facebook, on other sites?
 Please note: General terms and searches are better than very specific or topical ones for revealing a filter bubble (if they are too specific, there is less scope for algorithmic interference)

2. Efforts to mask identity in order to get outside the filter bubble, or minimise its effects, such that a comparison can be made with unmasked search engines, newsfeeds, or sites.
Some suggestions:
 Simple option: using a public computer or some other device that has not been used (or rarely used) previously.
 More complex option: using the TOR network, or a VPN.
 Please note: Turning cookies off or turning private browsing on does not generate good results.

II. Structure
No separate introduction is required. Subheadings may or may not be used. Refer to Points of Style document for tips on how to write the report.

Method
The method should outline the procedure used (a good idea for this section and the next is to take notes during the process, a bit like describing a chemistry or physics experiment in high school). No penalty will be given to students who do not use complex methods such as TOR: all students will be evaluated similarly, on how well they document whatever methods they used.

Results
This section should present the results of the conducted tests; leave comments and analysis for the next section.

Discussion and analysis
Discussion and analysis should look for general theories or truths drawing on your results. Ideally there will be some conclusion about how strong the evidence is for a filter bubble, and further analysis of what content is included / excluded by it, yielding a partial representation of the world. This section could also deconstruct the elements of any filter bubble that was found to be occuring, roughly divided into self-selection and algorithmic selection.

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