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How the Evergreen Index Ranks Interest in Companies [v1 & Open Source Repo Notes]

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The Evergreen Index measures how companies rise and fall in the internet’s consciousness. HackerNoon - via the company database and technology story library - possesses rare insights into what companies to keep an eye on. We then fulfill the company’s digital footprint with api calls to top industry data about news mentions, social media discussions, and website traffic.


Evergreen Index Real-time Variable Inputs


The top variable input is interest in the company on HackerNoon, this accounts for 40% of a company’s Evergreen Index ranking. Accounting for the rest of the variable inputs - at 20% weight for each - are website ranking, social media mentions and news mentions.


Evergreen Index Input Variables (+ weight)=

  • (.4) Reader Interest on HackerNoon
  • (.2) News Mentions Around the Web
  • (.2) Social Media Discussion Levels
  • (.2) Real Traffic to Website and App


Rationale behind the weights: What we have deep knowledge of is the heaviest variable, but it’s less than half of our decision making. By working outwards from site traffic to social media discussion and to news story mentions, we are able to measure where the rest of the web thinks this compare is headed, or at the very least, we are able to confirm that the rest of the web is interested or not interested in where the company’s headed.


[ How The Evergreen Index Works ] (hackernoon.com/evergreen-index

Everyday at noon, HackerNoon Ranks every company from 1 to X thousand based on the new day’s input across interest on HackerNoon, site traffic, social mentions and news mentions.

[Interest on HackerNoon]( hackernoon.com/companies/reader-rankings)

Company News Page Viewership via HackerNoon/Cloudflare Analytics



Source: github.com/hackernoon/evergreen-index/reader-rankings



[Website Traffic]( hackernoon.com/companies/traffic-rankings)

Website Ranking via Ahrefs/SEMrush/other API



Source: github.com/hackernoon/evergreen-index/traffic-rankings



[Social Media Activity]( hackernoon.com/companies/social-media-rankings)

Social Media mentions, activity & community engagement via [ ] API


Source: github.com/hackernoon/evergreen-index/social-media-rankings


[News Mentions]( hackernoon.com/companies/news-rankings)

  • Around the web via Bing News API

Source: github.com/hackernoon/evergreen-index/news-rankings