[Socialgist] Latticework partners with Socialgist & Quora to bring Investor Data to Snowflake Marketplace

A new era of data accessibility reveals a large, active, & welcoming community of beginners and experts

At Socialgist we recently announced our strategic partnership with Quora, enabling an entire ecosystem of businesses to access privacy-safe business insights from the Quora community for the first time ever via API. Today we’re announcing that this same Quora dataset is also available via the Snowflake Marketplace, empowering analysts to ask and answer questions using traditional SQL and any SQL-compliant business intelligence tools.

It’s a big deal. Traditionally, the process for understanding changes in sentiment in long-form, conversational, unstructured data sets was a laborious one. Analysts needed to write code to consume API’s, and to leverage machine learning toolkits to extract meaning.

But now analysts can simply scan through hundreds of thousands of Quora conversations using simple SQL statements, all from a point and click interface inside of the Snowflake Marketplace.

Let’s say you want to understand changes in investor sentiment over the year, across multiple different investing topics. Before, analysts had to harvest data from multiple API’s, build a data warehouse, and figure out how to query across massive and unwieldy data sets, all before asking a single question.  But with the release of Socialgist’s new “Quora Investing Questions & Answers” Data Share in the Snowflake Marketplace, now all of this data comes pre-structured and ready to query.  Upon approval, the Share is instantly available in your Snowflake environment.  There’s no messy ETL process, you can query data directly from Socialgist’s database on Snowflake. 

Analysts can simply perform keyword searches across Question & Answer text, peruse pre-categorized NER Topics, and scan across entire verticals.

Let’s say they were looking for information around: When did interest in SPAC’s begin to peak in 2020 and what were people’s chief concerns?  As an analyst, all you’d have to write is the simple SQL statement below:

select *
from "QUORA"."QUORA"."QUESTION_ANSWERS_LIST"
where vertical = 'investing'
and (title ilike '%spac%' or content ilike '%spac%')

You’d quickly be presented with over 30,000 conversations about SPAC’s.  You could quickly see that the conversation around SPAC’s peaked in July of 2020 (49 brand new Quora Questions were asked on July 29th, almost double the average volume throughout the year).

Quora datasets include all of the interesting metadata about conversations, such as Answer counts, Follow counts, and even Page View counts for each question.  Analysts can quickly search and sort through these dimensions and quickly find the most active conversations.

For example, let’s say you’re interested in when conversations about “Risk” were beginning to percolate.  On October 13, of 2020, there were 27 brand new Quora Questions created about risk in the market, about 4.5 times the average for “risk” (unsurprisingly, the S&P 500 saw a 7.4% market drawdown that same week).

You could also see the most answered question about risk was “If one intends to retire at age 65 and are currently 52, should they leave their 401k in "high risk"?”.  

Whereas the most viewed question about risk was “Is it possible to have low risk and high returns when investing?”

Really the only limits to finding insights is the analysts’ imagination.  In fact, it would be very simple to see historical ebbs & flows in interest across a whole variety of topics.

Below we can see how Quora conversations ebbed and flowed across Bear Market, Risk, Alpha, SPAC, and Cryptocurrency subject matter.  Quickly scan for seasonal trends, find baselines, identify peaks, and even see burgeoning topics as they break into the mainstream.

You can clearly see that the conversation around Snowflake surged right before their record-setting IPO in mid-September of last year.

Even if you’re not sure which trends you’re looking for up front, Quora’s topic enrichment layer empowers you to scan across tens of thousands of industry Topics with almost no effort, and to pinpoint emerging investor trends that were otherwise not on your radar.

So if you and your teams are interested, you can submit a request via the Snowflake Marketplace.  And once your application is approved by Socialgist, your entire team can get started querying the enormous Quora dataset, across an expanding set of verticals including Investing, Entertainment, Technology, and Automotive.

If you’re interested in learning more, please check out the Quora Data Program listings https://www.snowflake.com/data-marketplace/?_sf_s=socialgist