Difference between revisions of "AY1516 T2 Team AP Analysis PostInterimPlan"

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==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica;  border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Facebook Graph API</strong></font></div></div>==
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==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica;  border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Facebook Graph API (Post Interim Plan)</strong></font></div></div>==
  
 
<p>Apart from analysing one of SGAG's popular social network Twitter, we plan to leverage the Facebook Graph API. Drawing from our experience using the twitter API, we are looking to crawl Facebook data in a similar fashion, crawling, retrieving and aggregating post-level Facebook data. Hopefully, this process can yield conclusive results about the SGAG's social network (likes, shares, etc) on Facebook. </p>
 
<p>Apart from analysing one of SGAG's popular social network Twitter, we plan to leverage the Facebook Graph API. Drawing from our experience using the twitter API, we are looking to crawl Facebook data in a similar fashion, crawling, retrieving and aggregating post-level Facebook data. Hopefully, this process can yield conclusive results about the SGAG's social network (likes, shares, etc) on Facebook. </p>
  
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==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica;  border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Approach</strong></font></div></div>==
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==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica;  border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Approach (Post Interim Plan)</strong></font></div></div>==
  
 
<table rules="all" width="80%" cellpadding="6" cellspacing="3" style="margin: 1em auto 1em auto; font-weight: normal;  border-style: solid">
 
<table rules="all" width="80%" cellpadding="6" cellspacing="3" style="margin: 1em auto 1em auto; font-weight: normal;  border-style: solid">
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</table>
 
</table>
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==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica;  border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Data Retrieval</strong></font></div></div>==
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Constructing the graph from scratch involved the usage of python code to retrieve posts from SGAG's Facebook account for posts dating back 10 months. This involved connecting to the Facebook graph API programatically to formulate a csv file that resembles this structure:
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<table rules="all" width="80%" cellpadding="6" cellspacing="3" style="margin: 1em auto 1em auto; font-weight: normal;  border-style: solid">
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<tr style="background-color:#E1F4FF;"><th>Post ID</th><th>List of Likers</th><th>List of Commenters</th></tr>
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<tr><td width="10%" border="1" align="center">378167172198277_1187053787976274</td>
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<td width="30%" border="1" align="center">10206930900524483;1042647259126948;10204920589409318; ...</td>
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<td width="60%" align="center">10153979571077290;955321504523847;1701864973403904; ...</td></tr>
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</table>
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Where each user ID in List of Likers and List of Commenters are separated by a semicolon, and tagged to each post.

Revision as of 16:49, 9 April 2016

Team ap home white.png HOME

Team ap overview white.png OVERVIEW

Team ap analysis white.png ANALYSIS

Team ap project management white.png PROJECT MANAGEMENT

Team ap documentation white.png DOCUMENTATION


Data Retrieval & Manipulation Findings Post interim plan


Facebook Graph API (Post Interim Plan)

Apart from analysing one of SGAG's popular social network Twitter, we plan to leverage the Facebook Graph API. Drawing from our experience using the twitter API, we are looking to crawl Facebook data in a similar fashion, crawling, retrieving and aggregating post-level Facebook data. Hopefully, this process can yield conclusive results about the SGAG's social network (likes, shares, etc) on Facebook.

Approach (Post Interim Plan)

StepExpected ResultNotes
1 Collect all post data
  • Get all posts of SGAG on SGAG page, preferably all posts from 2 years ago to date
  • For each post, look out for 'Like' count, and when Graph API 2.6 is out, look out for the other Facebook reactions as well
2 All user objects for each like, for every post
  • For each follower, explore whether privacy options by users will limit us to further classify these user objects
  • Analyse 'Like' count per post, and if possible chart 'Likers' social network on a post-level basis
  • Manually categorize posts, like what we did for Twitter, and possibly prune them, to further refine insights
3 "Comment-Level" per post and number of shares on a "user-level"
  • Analyse posts by its comments
  • Are posts that are highly commented popular?
  • Analyze users who actually "Share" sgag's posts, and their connection with other users

Data Retrieval

Constructing the graph from scratch involved the usage of python code to retrieve posts from SGAG's Facebook account for posts dating back 10 months. This involved connecting to the Facebook graph API programatically to formulate a csv file that resembles this structure:

Post IDList of LikersList of Commenters
378167172198277_1187053787976274 10206930900524483;1042647259126948;10204920589409318; ... 10153979571077290;955321504523847;1701864973403904; ...

Where each user ID in List of Likers and List of Commenters are separated by a semicolon, and tagged to each post.

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