Every week we analyze the most discussed topics on Twitter by Data Science influencers.
The following topics, URLs, resources and tweets have been automatically selected by a custom topic extraction model. Want to know more? Jump at the end of this article!
This Week Overview
This week, Data Science influencers have:
- Shared free resources to learn more about Data Science recommending books, e-books cheat sheets and libraries.
- Reacted to the capitol riots in the USA.
- Discussed about the threats of artificial intelligence (AI)
Here are all the details for each topic:
Free Data Science Resources
This week, several influencers provided useful resources to learn more about data science for free.
Dr. Ganapathi Pulipaka provided several cheat sheets on What is Machine Learning, recommended free Machine Learning books, 100+ free Data Science and Python e-books and many more we can’t even list them all.
Kirk Borne took a different approach and selected two coding books for Data Scientist on R and Python as well as Mike Tamir who picked out an Introduction to Linear Algebra for Applied Machine Learning with Python.
Nicholas Vadivelu publicised PlotNeuralNet, a library to generate LaTeX visualizations for neural networks and Francois Chollet shared a 50 lines text generation model built on top of Keras!
Finally, some sound related data science resources shared by Mack and Ed Kwedar about NLP using quantum computers and an approach to categorize music by similar audio features.
The Capitol Riots In The USA
As expected, the current political crisis in the USA and more especially the recent Capitol riots in Washington DC generated a lot of reactions on Twitter. Data Science influencers took a stance on this exceptional political event and clearly expressed negative opinions against Trump and their supporters.
While some of them openly asked Trump to be removed from office, mocked the decision from Rep. Chris Stewart to not certify the election and retweeted news of Trump accounts being suspended from big tech companies like Shopify, as well as the news from the Professional Golfers Association to cancel the 2022 PGA Championship at Trump Bedminster, others denounced Arnold Schwarzenegger comparing the storming of the US Capitol Building to Kristallnacht.
Others reacted to tweets about how the media played a role in the rise of Trump, his ideas and the Capitol riots, highlighting how predictable all of this was, wondering ironically how come some journalists are still asking if this was planned or sharing Michelle Wolf quote on how the media had financial interest in publicising Trump.
Washington Police was also accused of letting people in or not using tear gas against protesters in some tweets, which led some influencers to go into more polemic posts asking to abolish the police.
The Threats Of AI
Data science influencers talked about the threats of artificial intelligence on our daily lives. In particular, they described how it is creating a fake world, wondered if AI could take over the world, control your mind or feel emotion, warned about ethical consequences such as discrimnatory biases and debated if fairness can be automated with AI itself?
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They also shared concerns that it will take away jobs. Not only it may threaten architect’s jobs, taxi drivers or truckers jobs with driverless vehicles but it may as well replace Data Scientist themselves!
The Methodology
In order to find Twitter most discussed topics within the data science community, we created a whole pipeline combining influencers analysis, data extraction and NLP using the BERTopic Python library, a topic modeling technique that leverages:
- Sentence Transformers, to obtain a robust semantic representation of the texts
- HDBSCAN, to create dense and relevant clusters
- Class-based TF-IDF (c-TF-IDF), to allow easy interpretable topics whilst keeping important words in the topics descriptions.
To fit our use case we slightly revisited Marteen Gootendorst’s original BERTopic library available here and on Github. We will later publish an article detailing our methodology.
Special thanks to the Atoti team for making this possible, in particular Ariel Ibaba
