Row 68355

Row ID: 68355 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 68355 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

I think you hit many of the top data science influencers I'm aware of.

If you broaden "data science" to analytics (eg I'm an applied statistician, but I might mainly work in sql, prefer spreadsheets and bi tools), there is a much larger group.

For what it's worth, I've been thinking about this and am happy to share my thoughts -- I'm certainly no authority on the topic though.

1. Firstly our space is already very small and niche. There are huge skin care influencers, but there's also a ton of people with skin. 2. Proportionally, fewer data scientists want to become an influencer:

I think there's a large barrier to entry, since the opportunity costs for data scientists to move to "influencing" full-time is so high. Why quit your comfy, well-paid, fancy, often-interesting research and/or corp job to make pennies on the dollar sharing content on social platforms? And so, there's just a smaller pool of people who want to create and share content.

3. Data science influencers grow slowly, and it's early days.

Also, I think these folks audiences and reputation will grow much more slowly then in less-niche, very broad topics. I could be very wrong, but I see the data science influencer crowd as being biased towards folks who are very good communicators, more charismatic, and they value sharing with others what they've learned. While many folks who are more technically minded (by that, I mean people developing new methodologies, contributing to packages & tooling, writing the most popular books and text-based resources I'm aware of) are -- no offense -- less skilled on-camera, and often couldn't care less about social media beyond blogging or giving conf talks. And so those technical folks, who we might prefer make more content, tend to make cool stuff, write blogs, books and talk at conferences. Their content is very technical (harder for broad audiences to appreciate), content that's unlikely to go viral.

I think that means these the aspiring data science influencer crowd mainly grow audiences first with novice/learners, and people considering applied stats as a major or career. Therefore these folks won't have much of a reputation until their audiences become more senior.

Josh/StatQuest (the biggest I can think) I think has only been full-time for 2-4 years now. I personally think Josh is amazing, a really lovely person, makes great videos and has a fanbase that agrees ... but he's \["only" growing at 20k a new subs a month\](https://socialblade.com/youtube/user/joshstarmer). So, that's an "it's very early days" argument, for why we don't see many big folks.

That is, while a travel influencer might be able to grow quickly, in the ds space, folks with no reputation will probably take a long time and a lot more work to grow a sizable audience.

4. The most popular "data science content" is domain-specific, & domain experts talk about our work better than we do.

And then I feel no-one has really cracked the format to make data science in-and-of-itself more broadly interesting. I feel the most "viral" data science'y content tend to be interesting plots (see r/dataisbeautiful, chartr-daily) and great data journalism. The content that really blows up is often attached to a specific domain.

For instance, 538 has amazing data scientists sharing their work, but Nate Silver isn't know as a "data scientist", he's well know an elections modeler and sports analytics expert.

Just my recent thoughts! Maybe I should have made this into a video for the tiktok.

Field	Value
text	I think you hit many of the top data science influencers I'm aware of. If you broaden "data science" to analytics (eg I'm an applied statistician, but I might mainly work in sql, prefer spreadsheets and bi tools), there is a much larger group. For what it's worth, I've been thinking about this and am happy to share my thoughts -- I'm certainly no authority on the topic though. 1. Firstly our space is already very small and niche. There are huge skin care influencers, but there's also a ton of…
label	r/datascience
dataType	comment
communityName	r/datascience
datetime	2024-05-23
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Raw Record

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  "text": "I think you hit many of the top data science influencers I'm aware of.\n\nIf you broaden \"data science\" to analytics (eg I'm an applied statistician, but I might mainly work in sql, prefer spreadsheets and bi tools), there is a much larger group.\n\nFor what it's worth, I've been thinking about this and am happy to share my thoughts -- I'm certainly no authority on the topic though.\n\n1. Firstly our space is already very small and niche. There are huge skin care influencers, but there's also a ton of people with skin.\n2. Proportionally, fewer data scientists want to become an influencer:\n\nI think there's a large barrier to entry, since the opportunity costs for data scientists to move to \"influencing\" full-time is so high. Why quit your comfy, well-paid, fancy, often-interesting research and/or corp job to make pennies on the dollar sharing content on social platforms? And so, there's just a smaller pool of people who want to create and share content.\n\n3. Data science influencers  grow slowly, and it's early days.\n\nAlso, I think these folks audiences and reputation will grow much more slowly then in less-niche, very broad topics. I could be very wrong, but I see the data science influencer crowd as being biased towards folks who are very good communicators, more charismatic, and they value sharing with others what they've learned. While many folks who are more technically minded (by that, I mean people developing new methodologies, contributing to packages & tooling, writing the most popular books and text-based resources I'm aware of) are -- no offense -- less skilled on-camera, and often couldn't care less about social media beyond blogging or giving conf talks.  \nAnd so those technical folks, who we might prefer make more content, tend to make cool stuff, write blogs, books and talk at conferences. Their content is very technical (harder for broad audiences to appreciate), content that's unlikely to go viral.\n\nI think that means these the aspiring data science influencer crowd mainly grow audiences first with novice/learners, and people considering applied stats as a major or career. Therefore these folks won't have much of a reputation until their audiences become more senior.\n\nJosh/StatQuest (the biggest I can think) I think has only been full-time for 2-4 years now. I personally think Josh is amazing, a really lovely person, makes great videos and has a fanbase that agrees ... but he's \\[\"only\" growing at 20k a new subs a month\\](https://socialblade.com/youtube/user/joshstarmer). So, that's an \"it's very early days\" argument, for why we don't see many big folks.\n\nThat is, while a travel influencer might be able to grow quickly, in the ds space, folks with no reputation will probably take a long time and a lot more work to grow a sizable audience.\n\n4. The most popular \"data science content\" is domain-specific, & domain experts talk about our work better than we do.\n\nAnd then I feel no-one has really cracked the format to make data science in-and-of-itself more broadly interesting. I feel the most \"viral\" data science'y content tend to be interesting plots (see r/dataisbeautiful, chartr-daily) and great data journalism. The content that really blows up is often attached to a specific domain.\n\nFor instance, 538 has amazing data scientists sharing their work, but Nate Silver isn't know as a \"data scientist\", he's well know an elections modeler and sports analytics expert.\n\nJust my recent thoughts! Maybe I should have made this into a video for the tiktok.",
  "label": "r/datascience",
  "dataType": "comment",
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  "datetime": "2024-05-23",
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}

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Entry Information

Entry ID: 68355
Repository: Axioma AXP
Dataset: arrmlet/reddit_dataset_36
Total Entries: 100,000