We know all too well that without proper care online communities can easily become bubbles, effectively becoming echo-chambers of opinion that, unchecked, can leave unwary users with a very distorted view of how real world opinion differs from that in their online community.
We seek out social contact within a relatively narrow set of views and ideologies; we are naturally attracted to people who share our views and actively shun those who don’t. This has, and is, playing out in the political world at the moment with many “remain” voter left reeling after the UK voted for Brexit. For me personally this meant I could debate and engage with only one Brexit voter in my network – did this really help me shape my opinion and attitudes? Did I affect anyone elses as a result of my discussions on the subject, or did we simply reinforce our own beliefs? The blunt truth is that I comprehensively failed to either appreciate or engage with any other viewpoint apart from those almost identical to my own. On the political spectrum the two camps were ideologically so far apart that this polarisation of views was reinforced on both sides and arguments that seemed obvious to one side failed to land on the other. This left the Remain vote in disarray as they failed to appreciate their own failings. In the US we are also seeing this play out with the lead of 60 / 70 points, predicted by many for Clinton, failing to materialise as Trump supporters continue to be disengaged by any alternative despite the Republican’s many “gaffes”.
I won’t dwell on it here as this echo-chamber effect has been been discussed by many, a particularly good article by David Byrne is well worth reading.
Within data visualisation, my field of interest, it is easy to see the same issues play out. In the data viz world online communities have typically been built around software / solutions; Tableau, Qlik, PowerBI, D3, R to name a few; as well as having a more general solution agnostic communities typically flourishing around experts / researchers or special interest such as sports data . Visualisations that might not get a second glance in one community can be lauded as the best thing since sliced bread in others – often praise revolving around the technical difficulties of producing the visualisation as opposed to their validity as a useful / interesting visualisation or analysis. The echo of what is “good” / “bad” can vary wildly between solutions and communities (though typically a hatred of a pie chart unites communities in a common rallying cry).
For new members of the data visualisation community it can be very easy to become distracted by these echoes and feel that certain techniques or visualisations offer more value (based on feedback from the community) than others. Of more concern is that without checks and balances communities can easily alienate those who don’t share similar opinions to those in the “bubble” leading to an increasingly narrow set of viewpoints, all reinforcing each other.
How to avoid the Bubble
With this in mind I wanted to offer some tips to the discerning social media user in the Data Visualisation world, new or old, on how to avoid the bubble effect and ensure your timeline remains diverse.
- Remember you are in a bubble
Simply being aware of the fact that our online communities don’t reflect the real world is a start. Remember it. Try and actively switch your viewpoint to that of an outsider at regular intervals in order to try and see your community through a different lens.
- Be yourself
Online communities are seen y some as a means to end career and learning-wise but that doesn’t stop you developing an online personality and diversifying your posts. Showing people who you are outside the community will help people relate in a different way to your online self and give them confidence to challenge your views if they want to
- Diversify who you follow
Okay so this one is fairly obvious but it needs to be said: don’t just follow people who are likely to agree with you. Go out of your way to look for communities in other areas away from your chosen data visualisation solution – use Twitter lists if you wish to ensure your timeline doesn’t become cluttered.
Follow a wide range of genders and ages, go outside your normal circles, a diverse network of followers will server to provide a range of views to counterbalance yours.
- Diversify your followers
So this is harder, but you really need to make sure you have a wide range of different viewpoints in your follower list. That way your posts are more likely to be debated as opposed to be accepted at face value. How do you do this? Post on different subjects away from your core solution, e.g. if you primarily post about Tableau then try to keep your posts generic, or try building visualisations in a range of different software to ensure you attract followers from different software vendors / solutions. Build a broad base of content but remain focused to ensure you appeal to your broader audience. Don’t be afraid to lose followers in this manner – personally I’d rather one follower who offers a counterpoint to my views than two who don’t.
- Diversify your inputs
There’s really no better way to open up your horizons than by drawing inputs from across multiples streams; Reddit, Twitter, LinkedIn, Facebook, Books, Blogs, Conferences, Periscopes, Meetups are all ways to try and seek out new contacts. Try to actively look for communities that do things differently, or might even actively disagree with you, and try to shift your perspective to theirs. There is no right or wrong solution and altering your perspective can make the world seem a very different place.
- Challenge the status quo
It’s okay to disagree now and then if you do it the right way – there’s a balance between being “that guy” and debating productively with someone who is willing to listen. Be especially careful of providing a dissenting voice if you’re new to a community e.g. a Qlik user in the Tableau community might see his/her views dismissed. However, don’t disagree on everything, it get’s tiresome in communities to see constant disagreement (further reading here from Ben Jones).
- Avoid being a fanboy / girl
In the same way then agreeing, retweeting and liking everything adds very little value to a community. Work out why you’re in the community; do you want to help new users, publish your own content, get help to solutions? Develop an online profile / personality around those interests and share content while adding your own comments. Followers will engage much more with cultivated, meaningful content that you have added value to.
- Don’t take feedback too much to heart
Positive feedback feels great, it’s sometimes overwhelming to have your visualisation praised by the community and it’s easy for it to go to your head but be aware that that is only likely to be one viewpoint, albeit a shared one. Learn to critique your own visualisations and rely less on likes / retweets / Viz of the Day as a way of judging a projects value.
Similarly just because a project gets negative (or worse no) feedback then that doesn’t mean it doesn’t have value. Social Media can be very fickle, things on a populist theme will get much more attention than anything of genuine business value.
- Seek out feedback from alternative sources
Seek out alternative feedback from different communities or on different platforms. One of the best ways is to ask for honest feedback from one or two trusted contacts / experts privately where they are more likely to give your work time and energy as opposed to glancing over it, or simply hitting the retweet button. The value of one meaningful critique like this is not to be underestimated, 140 characters is isn’t enough to get any meaningful feedback and so many people won’t bother.
- Don’t just take my word for it
Do you agree? Look for other methods of avoiding the bubble online, a lot has been written about the social media bubble. Discuss, comment, argue and debate with me – I’d love to hear from you. I’m happy to be wrong.
What does this mean for me personally?
I’ll be the first to admit I’m well inside the bubble myself. Very few of my contacts and peers in the world of data visualisation come from outside the Tableau world. I rarely use any other solution to build data visualisations and I fail to engage with any media away from Twitter and LinkedIn professionally. I could do a lot more.
Over the next few months I need to ensure I broaden my horizons using the tips above, work with new people and seek out their opinions. I intend to work with new communities and with new solutions to see the world from their point of view….and I’ll be richer for it.