Brainstorming MCSN

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Please add your contributions to this page. Each contribution in 4 parts (but feel free to leave these sketchy...)

  1. Phenomenon from MCSN
  2. Research question to ask about this phenomenon
  3. Model: How would you frame this question in terms of social networks?
  4. What sort of method can you propose for answering it? (how would you gather and analyze the data?)

Place four dashes between entries, and sign them so we know who contributed what.

These ideas might develop into your projects, but at this stage feel free to just brainstorm.

Not sure how to edit wiki pages? It's easy. See How to write these wiki pages. For now, just read "Basic text editing".

For example, here's one from Michael:

  1. Phenomenon: Musician-celebrities on Twitter
  2. Research question: how does the structure of Twitter connections differ by music genre - or does it?
  3. Model: musician-celebrity is a vertex, as is everyone they follow. Lines are arcs, defined by "following".
  4. Method: extract these egonets from Twitter, and analyze density (to what extent do those they follow actually follow each other?)

  1. Phenomenon: Artists on Facebook
  2. Research question: How artists attract more fans - just a friend of friend or by the art genres?
  3. Model: Artists and everyone that as a fan is vertex, by having the fans following the artist.
  4. Method: Analyze the specialties of the artist and the interest of the fans.

Chee Meng Low

From Alyssa Baker

  1. Phenom: Amateur musicians gaining exposure through "friends" via social network platform (Facebook, etc).
  2. Research Question: How does sharing music with friends via SN serve to elevate an amateur musician's potential career or popularity? Is it effective?
  3. Model: Amateur musician as vertex. SN friends that have been exposed to their music are also vertices. Lines are mono- and bi-directional arcs, representing those that have shared (forwarded) the musician's performances/songs with their SN friends, via SN platform.
  4. Method: Analyze a correlation (if any) between the success of the musician's career/ SN popularity, and how many people have been exposed to or have forwarded the musician's performances to other SN users.

From Nadine Aulin

  1. Phenomenon: Musicians gaining popularity and exposure through "hits" on youtube.
  2. Research Questions: How can a musician or upcoming musician achieve popularity or a career by uploading their songs onto youtube?
  3. Model: The musician is the vertex. The "hits" or amount of times the song has been viewed by any number of people and any amount of times by individuals are the lines. Lines represented can be "likes","dislikes" or "shared". These lines would be mono-directional and can increase depending on how many people are exposed to the song and how many times each person listens to it.
  4. Method: Analyze the correlation between the musicians success with their youtube video and how many hits they have received that are "likes", "dislikes", or "shared".

From Lauren Baril

  1. Phenomenon: Musical events marketed through social networks (ex. Facebook).
  2. Research Question: Is the use of social media in the marketing of musical events (‘word of mouth’ through SN friends) more effective than traditional marketing vehicles (ex. advertisements on billboards and in newspapers)?
  3. Model: The musical event is the vertex. Friends that have been exposed to the musical event are vertices as well. Lines are arcs (represent SN friends that have forwarded/shared the event with their friends).
  4. Method: Compare and analyze two similar kinds of events that have used different types of marketing. (*work in progress*)

From Jeffrey Andrews

  1. Phenomenon: Evolution of a fan base of a band on a social networking site (facebook, myspace, etc...)
  2. Research Question: How does a fan base of a band grow as they increase in popularity?
  3. Model: The Band is a vertex. Fans are vertexes. Lines and arcs are following.
  4. Method: Track the evolution of the network over time, by analyzing and comparing networks at different intervals.

From Raimundo Gonzalez

  1. Phenomenon: Followers of indie artists in Myspace and there degrees of involvement.
  2. Research: Are the different degrees of involvement in the link created between an indie artist and his follower?
  3. Model: Both followers and indie artist are vertices. Arcs represent internet browsing. Arcs are assigned various values from a predetermined scale which indicate the amount of internet traffic. The scale takes in account the amount of visits, the amount of time spent on each visit, song plays, videos views, etc.
  4. Method: Analyze and compare the values of the different arcs and create categories of followers.

From Allison Sokil

  1. Phenomenon: Track a number one electronic hit from country of creation to international hit status through international media sites/charts
  2. Research Question: How does social networking through the internet allow for electronic tracks from previously unknown artists to become international sensations?
  3. Model: Song is a vertex. Countries it hit #1 status in are vertices. Lines can be arcs or loops. Loops if a track is continually #1 in the international charts for weeks at a time.
  4. Method: Track #1 electronic song from country of origin, through networks of international dance music charts. Analyze the time span taken to create a number one from nothing, as well as, which countries were in its path. From there seeing if any other hit followed the same sn path.