June 27, 2013

Scraping for Semi-automatic Market Research

It was easy (Microsoft just updated their forum software!) to scrape Microsoft TechNet Forums and normalize the resulting information to have a better idea of each thread’s rank based on views and initial publication date. Knowing how issues are ranked can help a company choose what to focus on.

This code was used to scrape Microsoft TechNet’s forums. In the example below we scraped the App-V forum, since it is one of the application virtualization market’s leaders along with VMware ThinApp, and Symantec Workspace Virtualization.

These are the top ten threads for the App-V forum:

  1. “Exception has been thrown by the target of an invocation”
  2. Office 2010 KMS activation Error: 0xC004F074
  3. App-V 5 Hotfix 1
  4. Outlook 2010 Search Not Working
  5. Java 1.6 update 17 for Kronos (webapp)
  6. Word 2010 There was a problem sending the command to the program
  7. Utility to quickly install/remove App-V packages
  8. SAP GUI 7.1
  9. The dreaded: “The Application Virtualization Client could not launch the application”
  10. Sequencing Chrome with 4.6 SP1 on Windows 7 x64

The results show how frequently customers have issues with virtualizing Microsoft Office, Key Management Services (KMS), SAP, and Java. App-V competitors like Symantec Workspace Virtualization and VMWare ThinApp have similar problems. Researching markets this way gives you a good idea of areas where you can contribute solutions.

The scraper stores all the information in a SQLite database. The database can be exported using the csv_App-V.py script to an UTF-8 CSV file. We imported the file with Microsoft Excel and then normalized the ranking of the threads. To normalize it we divided the number of views by the age of the thread so threads with more views per day rank higher. Again, the scraper can be used on any Microsoft forum on Social TechNet. Try it out on your favorite forum.

Code

Prerequisites: lxml.html

The code is available at microsoft-technet-forums-scraping [github] . It was written by Matias Palomera from Nektra Advanced Computing, who received valuable support from Victor Gonzalez.

Usage

  1. Run scrapper-App-V.py
  2. Then run csv_App-V.py
  3. The results are available in the App-V.csv file

Acknowledgments

Matias Palomera from Nektra Advanced Computing wrote the code.

Notes

  1. This is a single thread code. You can take a look at our discovering web resources code to optimize it with multithreading.
  2. Microsoft has given scrapers a special gift: it is possible to use the outputAs variable in the URL to get the structured information as XML instead of parsing HTML web pages.
  3. Our articles Distributed Scraping With Multiple Tor Circuits and Running Your Own Anonymous Rotating Proxies show how to Implement your own rotating proxies infrastructure with Tor.

If you liked this article, you might also like:

  1. Nektra and VMware are Collaborating to Simplify Application Virtualization Packaging
  2. Automated Discovery of Social Media Identities
  • robmills

    Great article.

    I had to make one small change to the scrapper_App-V.py code to get it to run.

    In get_threads_url change ‘?outputAs=xml’ to ‘&outputAs=xml’