With the recent launch of the Quora Public Data Program we are excited to share an introduction into the type of content and interaction you’ll find from its 300+ million monthly visitors. In this post, we’ll take a look at ways of approaching your analysis of public Quora data and highlight what makes it a unique source of insight.
Quora is the leading knowledge sharing platform with questions ranging from the philosophical to practical. The focus is on shared information and experiences. There are a few Quora specific elements that are helpful to understand:
- Questions are tagged with relevant topic labels. This helps to organize conversations together and makes discovery of more relevant content easier.
![](https://blog.socialgist.com/hs-fs/hubfs/Quora%20Blog%20Draft-4.png?width=558&name=Quora%20Blog%20Draft-4.png)
- Answers are upvoted by the community pushing high quality responses to the top.
![](https://blog.socialgist.com/hs-fs/hubfs/Quora%20Blog%20Draft-3.png?width=520&name=Quora%20Blog%20Draft-3.png)
- Users are able to build public profiles complete with their areas of interest and expertise.
![](https://blog.socialgist.com/hs-fs/hubfs/Quora%20Blog%20Draft-2.png?width=638&name=Quora%20Blog%20Draft-2.png)
The recent Preparing For the Normal report on Quora highlighted several topic areas of growth during this unprecedented time. As fan of bread and baking, I was interested to see the jump in interest in Sourdough. Such a great example of the breadth of topics on Quora!
If I want to analyze this increase in sourdough related content further there are a few ways to compile a relevant dataset:
- Keyword Specific: look for mentions of “sourdough” across all questions, answers, and topics
![](https://blog.socialgist.com/hs-fs/hubfs/Quora%20Blog%20Draft.png?width=519&name=Quora%20Blog%20Draft.png)
- Utilize topics to find additional relevant questions and answers. In this example, beyond the Sourdough Topic I might want to expand and also look at:
![](https://blog.socialgist.com/hs-fs/hubfs/Quora%20Blog%20Draft-1.png?width=504&name=Quora%20Blog%20Draft-1.png)
- Identify experts in the area of Sourdough using the “knows about” section of author profiles
- Search for brands related to Sourdough: Whole Foods, King Arthur Flour
Once I’ve identified my dataset, the Quora specific metadata helps round out the picture. Examples include:
Analysis Question | Useful Metadata |
Which questions are getting the most traction? | number of views, follows, answers; can use these to create a customized ranking of questions |
Which answers are most resonating with the Quora community? | number of views, shares, comments, upvotes; can use these to create a customized ranking of questions |
Who are the authors influencing this conversation? | author profile info including number of answers by topic, upvoted answers, content views; for example, can identify who are the Sourdough influencers in the eyes of the community |
What is the context of the sourdough questions? | topic tags; for example, seeing an increase in the sourdough topic tag alongside the working from home tag |
What brands are being mentioned? | topic tags; for example, comparisons of flour brands |
How has the conversation and interaction level changed over time? | Initial posting date as well as any updates to questions and answers; for example, questions have long life spans and increase/decrease in activity as the larger conversation shifts |
These same approaches for identifying and analyzing a dataset are applicable across the wide variety of Quora content. Please reach out if you’d like to see the specifics for your industry or brand!