Participatory interactive graphics(?) are visualizations that are designed to change around data from individual readers. These graphics use information solicited from the user or the user’s computer as a lens through which complex data or very general data is presented. This kind of interaction is increasingly important in storytelling.

Here are 3 types of stories I have come across that fall into this category.

1. Calculators and searchable interfaces – These searchable or adjustable interfaces allow users to glimpse the larger underlying system by answering each user’s targeted questions. Examples: “How The Internet* Talks” and “Is It Better to Rent or Buy?”

2. Draw your own/quizzes – Soliciting educated guesses of trends from users to involve them in thinking about the logic behind trends and increase impact. Example:  “You Draw It: How Family Income Predicts Children’s College Chances“ 

3. Geolocating Users – Using ip addresses to geolocate users and automatically alter the view and accompanying text of the visualization to be centered around a user’s location. This is used in navigating general and comprehensive datasets that cover the whole country but are only of interest to most readers as smaller slices. Example: “The Best and Worst Places to Grow Up: How Your Area Compares” 

I think these types of interaction are not only an important tool for storytelling online, but can affect larger patterns for reading online for several reasons.
1. They might be more readily shareable across social media because of how specific they are to the interest of a reader.
2. Commenting is problematic on many online articles. I think using this specific type of interaction can potentially serve as a filter for comment reading, and provide constructive directions for comment writing and discussion among readers.
3. Finally, this kind of interaction could serve as a dynamic filter for customizing out links from the article and effect recommendations.

There are discussions to be had on whether the data gathered from interacting with graphics should be used for purposes of catering content. I’m not sure yet how I feel about editorial decisions that might be increasingly challenged by the metrics of social media and how this addition contributes to the discussion. I would like to know more about how feedback is currently weighted in the newsroom. Ultimately, this interaction may result in more stories being force fit into a data-centric model that is less good than what we have now. There are also definitely issues with the quality of the data being gathered from this type of interaction, which is an interesting area of study once there is a large enough sample size.

I do believe experimenting with this type of input is ultimately worth it and could change the way we look at readers and frame select stories in a positive way. Actively using reader input is a important concept for storytelling. It is not new, but it is adoption within interactive graphics has presented very exciting recent use cases and it is a topic that I would like to explore further.

The tool I’m interested in is Civil Comments.

How it Works

Their video offers a great overview of the system.

Civil Comments – How It Works from Civil Co. on Vimeo.

Why It’s Interesting

The Civil Comments tool provides an interesting intervention in the comments space, because it offers a unique but also intuitive answer to some of the key problems facing online content publishers when it comes to their comments.

1. The Expense of Moderating, Especially at Scale – many content publishers currently face a huge problem when it comes to moderating comments. Most moderation requires a human editor. Although many tools will automatically filter out abusive terms, it still takes a human moderator with judgment (and maturity!) to read user-flagged comments. For publishers who deal with heavy content volume, human moderation can be very expensive. By leveraging the power of the audience, Civil offers to make comment moderation free, and scalable. This is huge. The Civil interface is also pretty simple – it looks a lot like TripAdvisor’s or Amazon’s ratings, which are proven interfaces that people like to use.
2. Limiting incentives to abuse – the most thought-provoking claim that Civil makes is that they’re able to single out abusive commenters through this crowd-sourced system. I’m not entirely sure if that’s the case, but their initial run with Willamette week appears to have garnered some positive reviews. Although untrained folks may NOT always be able to filter out abusive comments, this crowd-moderated system raises some interesting questions about the incentives to post uncivil commentary. If comments are social, as many people (including Joseph Reagle of Northeastern, in his book on the topic) have suggested, then that begs the question: if only 1 or 2 people at most are going to see an abusive comment before it gets buried, will trolls even want to post abuse in this kind of system? Is the incentive to abuse lessened when there’s no audience? When it comes to mass troll attacks, Civil claims they have a system that will detect them.
3. Hierarchy? Values? By enabling a form of peer moderation, it’s possible that publishers who use the Civil system will send a positive message about the role that their community plays in setting the site’s values. It also marks the comment section as an independent space, one where both readers and journalists get to set priorities. At the same time, because readers get random comments to review, this peer moderation system might offer ways to avoid some of the bias (towards highly ranked commenters, towards familiar commenters, towards early comments) that other peer moderation systems are prone to (Lampe et al).

What it Won’t (Necessarily) Do

1. Eliminate issues of site-wide bias: Many moderators of peer moderated sites whom I’ve spoken to have mentioned that their sites have a particular political bias. I don’t see that Civil will address site-wide bias very effectively, especially considering that people tend to moderate comments more favorably when those comments reflect their own views.
2. Invite minority views/communities into conversations. One of the moderators whom I spoke with offered a compelling case study of how their site had drawn flak from trans members about transphobic language. The moderators made an executive decision to change community norms, and enforce those changes, even though the majority of site users weren’t as affected by the issue. Sometimes moderators might want to enforce values/etc that the community does not. How are these more subtle social norms introduced? How are they maintained and shown to new members who are visiting for the first time? It seems like the initial judgment made by the crowd might be a large-grained filter at best, and exclusionary at worst.
3. Protect identities and data. Conspicuously absent from the Civil Comments’ webpage: any mention of what happens to users’ comment data. Civil says that they offer analytics, which means that they must collect data or offer a data collection option. But publishers run their own ‘instances’ of Civil. How are those data stored and anonymized? Who has access? Will Civil turn around and sell that information? Particularly relevant in conjunction with point #2, but problems of online harassment in general.