Curiosity Bits Python Tutorial: Mining Facebook Fan Page - getting posts and comments

Created by The Curiosity Bits Blog (curiositybits.com)
The codes are provided by Dr. Gregory D. Saxton
Mining Facebook Page on Python
1

What data are available for mining?
• Posts: all posts on a Facebook page
• Content, posted time, included URLs, mentioned Facebook friends/pages, etc.
• Comments: comments on the posts
• Sender, content, posted time, etc.
• Engagement Indicators (we will cover this in an upcoming tutorial)
• The # of likes, shares and comments on a post
• The lifespan of a post: the time between sending the post and receiving its
last comment
2

The data are available through Facebook Graph API
• Use Facebook Graph API Explorer
(http://developers.facebook.com/tools/explorer) to get an access
token.
3

The JSON data will be stored on a SQLite database
• Like Twitter data, the raw output from Facebook API is in
JSON format. To see how the JSON output is organized, use
JSON Viewer (http://jsonviewer.stack.hu/)
- DOWNLOAD A JSON OUTPUT SAMPLE -
(https://drive.google.com/file/d/0Bwwg6GLCW_IPMWlL
Njd2NnplM1k/edit?usp=sharing)
4

A JSON will look like this on a web browser…
5

Copy the content of the downloaded JSON sample onto JSON Viewer
(http://jsonviewer.stack.hu), click “Viewer”
Download a sample JSON 6

Let’s get down to the Python code…
- DOWNLOAD THE PYTHON CODE -
(https://drive.google.com/file/d/0Bwwg6GLCW_IPbmNi
QW1EWGotd28/edit?usp=sharing)
7

Let’s walk you through each part of the script…part 1
Download a sample JSON
• These are necessary Python libraries. You
need to install them before running the
code.
• Not familiar with the installing? Review our
previous tutorial on how to install Python
libraries (pg.8) http://curiositybits.com/python-
for-mining-the-social-web/python-tutorial-mining-
twitter-user-profile/
8

Part 2: Create columns in the database for output variables
the name of a Facebook page; useful when
you are mining content from multiple pages
Page id, an unique identifier for a Facebook page
The URL to a Facebook page post
An unique identifier for a Facebook page post, formatted as Page ID_Status ID
An unique identifier for a Facebook page post, without page ID in it
The textual content of a post
9

When the page post is sent
When the post is retrieved from API
When the last comment is posted.
The type of the post – status, link, photo, video, etc.
The included URL(s) to a video
The name of the webpage that the included URL is linking to.
The Included URL(s) to a photo
Description of the webpage that the included
URL is linking to.
10

The number of mentions in a post
The mentioned page/people in a post
11

The entire JSON raw output, including information
not parsed to the existing columns
Comments (including sender, content and posted time) on
the first page
Comments on the second page and beyond
12

• The columns created here correspond to the output
variables returned by Facebook Graph API. See the
definitions of all output variables:
https://developers.facebook.com/docs/graph-
api/reference/post
13

Part 2: the parsed data look like this in a SQLite Database Browser
Not familiar with SQLite Database Browser? Review our first tutorial (page.
10) at http://curiositybits.com/python-for-mining-the-social-web/python-
tutorial-mining-twitter-user-profile/
14

Part 2: the parsed data look like this in a SQLite Database Browser– continued.
15

16

17

Click to see all comments.
Individual comments are separated
by the symbol ***
18

Q: Why are some columns entirely blank?
A: We have created more columns than we needed
for this round of data-mining. The additional
columns created are for the next iteration of mining
through which we will get Facebook engagement
indicators.
19

Part 3: Set up the access token in the Python script
Paste your own access token here.
20

Part 4: Set up the SQLite database in the Python script
Name your own database. The database
will be saved to the same folder as your
Python script.
Or try a complete file path, if you want to
save the database in a different folder. 21

Part 3: tell Python which Facebook pages to look for.
The numbers here are Facebook page IDs,
wrapped in ‘’, and separated by commas.
Each Facebook page will have an unique
page ID, which can be found in the page’s
URL.
22

You can also use page name if the
page name consists of only one
word.
23

BUT! Here is a catch:
if a page name contains multiple words, It is
recommended that you use numerical page id
instead. You can find the numerical page id in the URL
- the string of numbers after page name in the URL.
(e.g. https://www.facebook.com/pages/Spot-Coffee-
Elmwood/316579834919)
24

Part 4: run the script
Hit RUN and you
will see Anaconda
showing the
progress of the data
mining.
Not familiar with
Anaconda? Review
our previous
tutorial (pg. 3) at
http://curiositybits.com/py
thon-for-mining-the-social-
web/python-tutorial- 25

Lastly, a caveat….
If you encounter an error when running the script, a
database (though incomplete) may have been
created. You will need to delete the database file and
re-run the script, or change the database file name in
the script before the second run.
This script does not work on a preexisting database
file.
26

COMING UP NEXT…
GET FACEBOOK ENGAGEMENT INDICATORS
The # of likes, shares and comments to the posts, and the
lifespan of a post
Stay tuned to our Curiosity Bites Blog (curiositybits.com)
27

Curiosity Bits Python Tutorial: Mining Facebook Fan Page - getting posts and comments

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Curiosity Bits Python Tutorial: Mining Facebook Fan Page - getting posts and comments