
Analyzing 10 years of startup news with Machine Learning - feconroses
https://blog.monkeylearn.com/analyzing-10-years-of-startup-news-with-machine-learning/
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giardini
Was anything found that was not already well-known?

The article states:

"Wrap Up

... we’ve scraped hundreds of thousands of articles, created text
classifiers... and gotten insights from the results. _The only way to perform
an analysis like this is using machine learning and natural language
processing, since there’s no way we can get a person to read through and
interpret 270,000 articles. "_

I would have to say

\- there's always sampling, and

\- ask or read the reports of an expert, since they live in their respective
news spaces.

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rsteca
why asking an expert when you can ask the data?

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arca_vorago
Because you need an expert to make sense of the data? Which is why I am trying
to transition to data science from sysadmin at the moment. So I don't need no
stinkin middle men.

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untangle
Why is machine learning/NLP needed in this analysis?

The categories/keywords are well known, and I believe that simple statistics
would suffice to produce the type of results shown.

Of course, the text would have to be scanned and the dataset cleansed/filtered
first. But those techniques predate ML/NLP.

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edoceo
50+% of the articles they found are the self-published like noise around
fundraising and launch. Throws those obvious​ fluff out

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rrggrr
Why publish this and not public the code they used to interface with
MonkeyLearns API? Missed opportunity.

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wordvector
They published the code, you can check it out here:
[https://github.com/monkeylearn/startup-news-
analysis/blob/ma...](https://github.com/monkeylearn/startup-news-
analysis/blob/master/Try%20out%20the%20events%20and%20industry%20classifier.ipynb)

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kreetx
This is a nice summary for those who haven't spent the last ten ten years in
the startup sene, thanks!

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brilliantcode
Interesting to see fundraising articles peaking out in 2014, I think we are
definitely seeing a bear market.

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wimagguc
Couldn't it actually mean the opposite? If fundraising is not newsworthy, it
could also be because there are so many of those out there that fewer make the
cut.

