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

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In this part of the tutorial, we will teach you how to use Python to get all posts and comments from a given Facebook page.

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

  1. 1. Created by The Curiosity Bits Blog (curiositybits.com) The codes are provided by Dr. Gregory D. Saxton Mining Facebook Page on Python 1
  2. 2. 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
  3. 3. 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
  4. 4. 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
  5. 5. A JSON will look like this on a web browser… 5
  6. 6. Copy the content of the downloaded JSON sample onto JSON Viewer (http://jsonviewer.stack.hu), click “Viewer” Download a sample JSON 6
  7. 7. 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
  8. 8. 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
  9. 9. 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
  10. 10. Part 2: Create columns in the database for output variables 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
  11. 11. Part 2: Create columns in the database for output variables The number of mentions in a post The mentioned page/people in a post 11
  12. 12. Part 2: Create columns in the database for output variables 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
  13. 13. • 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
  14. 14. 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
  15. 15. Part 2: the parsed data look like this in a SQLite Database Browser– continued. 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/ 15
  16. 16. 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/ Part 2: the parsed data look like this in a SQLite Database Browser– continued. 16
  17. 17. 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/ Part 2: the parsed data look like this in a SQLite Database Browser– continued. 17
  18. 18. Click to see all comments. Individual comments are separated by the symbol *** Part 2: the parsed data look like this in a SQLite Database Browser– continued. 18
  19. 19. 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
  20. 20. Part 3: Set up the access token in the Python script Paste your own access token here. 20
  21. 21. 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
  22. 22. 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
  23. 23. You can also use page name if the page name consists of only one word. Part 3: tell Python which Facebook pages to look for. 23
  24. 24. 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) Part 3: tell Python which Facebook pages to look for. 24
  25. 25. 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
  26. 26. 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
  27. 27. 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

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