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07_twitter.Rmd
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07_twitter.Rmd
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# Using Twitter For Data Science
In a lesson in an earlier course we had you create a professional [Twitter](www.twitter.com) account. This is because Twitter is a very active place among data scientists. As a result, Twitter can be a great place to learn about new topics *and* to meet others in you field. *Additionally*, people often tweet about open positions at their companies, so Twitter can be a *really* great place both when you're looking to learn more and improve your skills *and* when you're looking for a job!
In this lesson we'll briefly discuss customizing your Twitter profile and then spend a fair amount of time delving into how to use Twitter effectively as a data scientist.
### Profile
As with every other platform we've discussed so far, you'll want to add a photo and update your Twitter profile. Your Twitter profile will contain less information than the other profiles we've discussed thus far, so we'll discuss all necessary steps of how to do so right away.
To update your photo, log into your [Twitter account](www.twitter.com). If you haven't yet uploaded a photo, you can do so, by clicking on the camera icon and clicking on "Upload photo" from the drop-down menu.
Navigate to the file you want to upload on your computer. In the window that appears, position and size your photo. When you're satisfied, click "Apply."
From here, click on the menu at the top right-hand of the screen and click "Profile" to navigate to your Twitter Profile.
Here, at the right, you can click on "Edit profile."
This will open up a box where you can write a short bio about yourself. This should just be a few words about your interests!
Here, we've included a few Twitter bios as examples. [@BecomingDataSci](https://twitter.com/BecomingDataSci?lang=en) is the Twitter account for the same person whose LinkedIn profile we looked at in the LinkedIn lesson. The other two are from two of the authors of this course. You'll note that they aren't very long and just briefly describe the Twitter user. Note that these can be edited at any time and will change over time.
You'll also want to include a link to your personal website in the "Website" box. Type the URL of your website there.
On these same three profiles whose bios we just looked at, you'll see that each has also helpfully provided their website URL within their individual Twitter profiles.
If you want to share your location, you can also include that under "Location," but this is not required. Once you've completed all the information you'd like your profile to include, click "Save changes" on the right-hand side.
### Who & What To Follow
Once you've got an updated profile, you're ready to start following people. It's best to keep this Twitter account as professional as possible. So, you may not want to follow your personal friends, musicians, actors, or other celebrities on this account. Rather, it's best to follow those who post information that will be helpful to you as a data scientist. Unlike LinkedIn where it may be best to limit who you follow right off the bat, it's ok to follow people you don't yet know on Twitter. Your goal should be to follow people you think 1) are interesting, 2) can teach you something, and/or 3) may post about things that would help you in your career!
As you search for individuals to follow, you come across someone you think you'd like to hear from, you should click the "Follow" button on their profile.
While you are *not* required to follow anyone, as someone new to the field of data science and who uses R, we're providing a list of people you may want to follow:
It can also be helpful to look through who these people follow to find other people you may be interested in following.
Finally, you can also search for people to follow using common hashtags, such as
[#rstats](https://twitter.com/search?q=%23rstats&src=typd) or [#r4ds](https://twitter.com/search?q=%23r4ds&src=typd). These two will put you in contact with a crowd that codes primarily in R. However, [#datascience](https://twitter.com/search?q=%23datascience&src=typd) and [#dataviz](https://twitter.com/search?q=%23dataviz&src=typd) will connect you with individuals interested in data science and data visualization generally. You can follow and unfollow people as you find helpful, so you aren't locked into following anyone forever.
### Tweeting
After you decide on who to follow, you'll want to check Twitter every so often to see what everyone has to say -- this can be a really great way to keep up with the newest data science news and to learn a lot!
As you begin to follow along and generate your own tweets, there are a few general guidelines that will make your Twitter experience a positive one:
1. keep it positive
2. avoid fights
3. support others
It's incredibly easy to allow discussions on the Internet to take a negative turn. But, avoid that instinct. Keep what you put on Twitter positive and avoid delving into Twitter feuds. Disagreements happen, but you should never make personal attacks or be unkind or rude to others on Twitter, regardless of what they do.
Also, Twitter can be an amazing and supportive place. So, try to promote your own work *and* support the work of others from your account. We'll discuss the details of this below!
#### Tweeting for Self-Promotion
When tweeting from your professional account, it is a *great* idea to tweet about work that you've done! Tweet about your projects, cool findings, or awesome visualizations. Include pictures of your awesome graphs, images from your blog post, and links to your work! When possible, include images that are compelling. These can help people visually remember your work!
One example of this is shown here. Jeff Leek wrote a book about [How to be a Modern Scientist](https://leanpub.com/modernscientist). This book includes information about how to use Twitter as a professional, so feel free to check it out for more details. But, as for the tweet, Jeff included an image, linked to where the content is, and stated that he released the book. What a [great and informative tweet](https://twitter.com/jtleek/status/718494461672734721) about his work!
#### Tweeting to Promote Others
You don't *need* your own, original content to build up a following on Twitter. Twitter can be a great place to **promote others' work**. You can gain followers by promoting others, being funny, being interesting, and curating others work effectively.
By tweeting about others' work, you'll have a record of all the things you find interesting, will be able to be a good community member (by promoting others' work), and will be able to add your thoughts *about* their work. Twitter is great b/c you can share others' work by adding your own commentary in your tweet! In your tweet, you should always **always cite the individual and link to their work**.
For example, here we see a case where Jeff tweets about a talk that [@CMU_Stats](https://twitter.com/CMU_Stats) was giving at a conference. He explains what was being discussed, includes [@CMU_Stats](https://twitter.com/CMU_Stats)' Twitter handle, and includes a picture!
Additionally, Jeff uses the hashtag #JSM2018. This allows individuals following this hashtag on Twitter to easily find the tweet. **Using helpful hashtags are another great way for others to find your twitter and follow you, even when they don't know you personally!**
#### How To Tweet
When you're ready to start tweeting, you'll want to click the blue "Tweet" button from your profile.
In the box that appears, you'll compose your tweet. You can add emojis, photos, GIFs, polls, and location to your tweets. The character limit on tweets is now 280 characters. This limit forces you to ensure your tweets are concise. It's good practice to convey a message clearly in a few short words.
As you generate tweets, you may have individuals comment on your tweets. Twitter can be a great place for quick discussions! However, here, we'll leave you with a reminder to keep your tweets professional from this account. Use your data science Twitter account as a professional social media account, which means that you never want to tweet anything inappropriate, rude, or unprofessional.
### Summary
In this lesson we discussed why Twitter can be a great place to learn more about data science quickly, how to use the platform to grow your network while having a positive experience, how to tweet for self-promotion, and how to tweet about others' work.
### Additional Resources
* [How to be a modern scientist](https://leanpub.com/modernscientist), by Jeff Leek
* _Phrasing: Communicating data science through tweets, gifs, and classic misdirection_ [video](https://rud.is/b/2018/08/27/simplifying-world-tile-grid-creation-with-geom_wtg/), by [Mara Averick]
### Slides and Video
[Automated Videos](https://www.youtube.com/watch?v=7Zw95c4bS2U)
* [Slides](https://docs.google.com/presentation/d/1iJ_ONxlP8SBZK6oAoeP7regVVmT5l9FIuZkMjAd-Y8Q/edit?usp=sharing)