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I find Twitter’s Polls useful. Agree/Disagree.

November 2, 2015

Introduction

Twitter recently introduced some new functionality.  Now you can create polls that stay open for 24 hours and allow you to tap into the Twitter community to get some answers to your burning questions.  Anyone on Twitter can vote for one of the two options in the poll and their choice remains anonymous.  I thought I’d have a little fun with them.

First a Few Words about how I use Twitter

Out of all of the tools that I use to keep up-to-date with what’s going on in the world of work, Twitter has to be the tool that I rely on the most.  I never use Twitter’s main site, other than to check out analytics from time to time, but I regularly use Tweetdeck to keep on top of several topics at a glance.

Tweetdeck screenshot

Tweetdeck lets you follow multiple Twitter streams at the same time.

When I want more of a summary of interesting articles being tweeted on a particular topic I also dip into Right Relevance to see what’s happening.

Right Relevance helps you to find articles and people on Twitter relevant to your interests.

Right Relevance helps you to find articles and people on Twitter relevant to your interests.

I also like to contribute to Twitter and tweet quite regularly.  I find it’s a great way to release random thoughts.  Crowdfire really helped me to find interesting people to follow and build up my own network.

Now on to the Polls

The first poll that I created was about Data Science.  In particular, it was about the job title of Data Scientist.  Are people happy with their Data Scientist titles?

Interestingly, only 55% of the respondents like their title.  Perhaps Data Scientist isn’t the sexiest job of the 21st century any longer.  I love my job but this fits with what I’ve recently seen in the community.  I increasingly see data science professionals from a range of companies becoming frustrated by the lack of clear meaning in their job title.  There are several roles that data scientists play (this recent study from Bob Hayes goes into detail) and lumping them all together as if they are one isn’t helpful.  It can also lead to envy and resentment across teams where one kind of data scientist is doing a very different job from another although upper management sees their contributions are equal.  Or, similarly, the same title means very different things in different companies and makes it hard to know what you’re dealing with when you see it on someone’s CV.

That result was interesting enough to encourage me to play more.  This time, I sent out a much more provocative poll to see what would happen.

This one got over double the respondents, 48 people voted for it over 20 for the first one.  Looks like I’m not alone in thinking that LinkedIn has a problem with recruiters.

I then went back to the topic of Data Science.  I was surprised in Bob Hayes’ study about Data Science roles that so few of them had a lot of knowledge about Machine Learning.  For me, machine learning is central to this job.  So, I opened up a new poll.

46 votes and a resounding yes with 80%.  So, although I don’t know who answered the poll, it looks like they have the same expectation as I do that Data Scientists should be experts in Machine Learning.

As a follow up from the first poll about whether Data Scientists like their job title, I then got to thinking that perhaps there’s a mismatch between what employees expect a Data Science job to be and what employers advertise as a Data Science job.

It turns out that people don’t think that Data Science job adverts describe the role well.  This might also be a reason for some of the unrest in the Data Science community.  It’s hard to keep good people if you aren’t clear and honest about what they will be working on during the interview process.

Finally, I wasn’t sure if the results of Twitter polls could really be trusted so I put it to the vote.

At the time of writing this post, the poll is still ongoing.  I wonder what the answer will be?

Are these Poll Results Credible?

In a word, no.  Anyone who knows the first thing about creating polls and surveys will know not to put much stock in the results of these polls.  There’s plenty of selection bias going on, no way to tell what the demographics of the respondents were, no way to ensure if the respondents were eligible to answer, no way to follow up and dig deeper and only a small number of respondents replied.  Some of these problems are particular to this test but others will apply generally to Twitter polls casting doubt on their general usefulness.

Let’s not let science get in the way of a little fun though.

Conclusion

Twitter polls are great, I’m addicted already!  I think I’m going to enjoy playing with them over the next few months.  I’ll be taking all of the results with a substantial helping of salt but hey, it’s fun.

Finally, as if it were planned.  I just noticed that I have sent 1,499 tweets so far.  That’ll make my next tweet, which will be about this blog post, the big 1,500!  Thanks Twitter!

High level Twitter statistics for my profile.

High level Twitter statistics for my profile.

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