As part of a homework for a Social Web course, I had to consider factors that research showed had an effect on user contribution on social websites (contribution can be anything from commenting, to rating, to making edits on a wiki page), and link them with popular design patterns used for crafting the user experience for such websites.
We primarily looked at the Yahoo! Design Pattern Library and tried to enhance patterns with more details, rationale for why they work, and more importantly, back our claims with credible references.
I didn’t find an equivalent design pattern in Yahoo’s library for the method of encouraging contribution that I was thinking of. I’ve seen this pattern used a lot on the Internet. I thought it might be good to give it some rigor and analyze why it works, in what situations it would work well, and how can it be improved. Below is the description of the Community Activity Awareness design pattern that I proposed (yes I know, I’m not good with names). The gist of the pattern is “When providing a user with the opportunity to contribute to the website, show information about how other users have responded (positively) to that particular contribution action”.
|Pattern name||Community Activity Awareness|
|Problem statement||People might ignore requests for contributing to a website (any contribution that increases social content on the site, such as rating, ‘liking’, or leaving comments) if they are not given information about the contributions of other members of the community.|
Image 1 Mockup of a particular implementation of the pattern
|Use when||Use this pattern when you want to tell the user about the activities and opinions of other members of the community about certain content on the website. This pattern can also be used to show popular trends amongst the community to the user. This pattern should also be used when the website wants to nudge the user into performing a certain action (such as commenting on an article).|
|Don’t use when||Do not use this pattern when you are looking to collect unbiased information, or the ‘wisdom of crowds’  about a certain topic, since this pattern divulges the opinion of other members of the community to the user before they (the user) have weighed in with their opinion. For example, this pattern should not be used for an online poll, or when ratings are used as votes (in the traditional sense) to select someone or something. The reason for this is the anchoring and adjustment heuristic  that we as people are prone to. This heuristic states that people’s estimates are influenced by suggested starting points (or anchors).|
|Solution statement||When providing a user with the opportunity to contribute to the website, show information about how other users have responded (positively) to that particular contribution action.|
|Solution description & examples||There are many ways in which information about the actions of other users (relevant to the current action that a user is about to perform) can be communicated. Obviously, it greatly depends on the nature of the action.
If the action is a simple ‘click’ operation (such as ‘vote up’, ‘vote down’, ‘like’), then information about the community’s activity can be provided in the following ways:
· Showing only the number of users who have performed the same action.
· Pointing out certain users (who might be connected to the user in some way; e.g. part of their social network) who performed the same action.
· A mixture of both of the above.
If the action is a little more demanding, such as writing a comment or a review, then information about the community’s activity can be provided in the following ways:
· Showing responses of users who performed the same action.
· Showing the number of users and their responses.
This pattern is nicely demonstrated by Facebook’s ‘like’ feature.
Image 2 shows the case of when the user is shown that another member of the community liked the content item they are looking at. The action in this case is ‘like’ (the button to perform this action is highlighted), and the information is presented just below the action button.
Another instance of this feature on Facebook is shown in Image 3.
This case simply shows the number of people who liked this content, and clicking on the number of people provides the user with more details about each person.
Another common use of this pattern is shown by the commenting system on YouTube, as shown in Image 4.
In this case the user is shown the total number of comments (83) and a paginated list of those comments below. The action to be performed in this case is to leave a comment on the video, and a link to perform this action (‘Sign in to post a Comment’) is shown right next to the information about the community’s response to that action.
A slight variant of this pattern can be seen on the Yahoo! Buzz website. Image 5 shows the widget that displays information on the latest user activity related to the ‘Buzz Up’ action (which is just a fancy name for a ‘vote up’).
The difference in this case is that the actual action (buzzing up content) is not available at the place this information is displayed. The user has to click on the article’s name to see the entire article along with the option to buzz it up. This implementation of Buzz Updates can be improved by making a ‘buzz up’ option visible when the user moves their mouse over a particular article’s section. This would allow the user to instantly perform the action that they’ve been told has been performed by other members of the community.
Another example of this pattern in a different context is shown below in Image 6.
This is the ‘Currently Active Users’ section on an online forum, which is located near the bottom of the page. This allows users to see which other members of the community are viewing the particular sub-section of the forum that they are viewing. In this case, the action is the actual viewing of content of a certain section of the forum (and possibly contributing to a discussion). Thus showing this information can have the effect of the user spending more time on a particular section of the forum that has a large number of active users. This is just speculation, and also based on my experience of being affected by this information; the user might think that since there are so many people viewing this section of the forum that there must be active/useful/popular discussions going on, and they would be more likely to look at topics in that part of the forum.
Another different incarnation of this pattern is in the ‘Trending Topics’ widget on Twitter, as shown in Image 7.
The action in this case is tweeting about a certain topic, and the information provided is what other people are tweeting about. This information is provided relatively close to the place of action (the ‘tweet box’ at the top of the profile page). This use of the pattern is different because information about individual users or the number of users is not given. Instead, the fact that a topic is a trend implies that a lot of people are tweeting about it. Thus it has a similar effect as displaying the number of people tweeting about this topic.
|Rationale||Kraut and Resnick discuss their claim that people will be more willing to contribute in an online community if they see that others are also contributing in . Their reasons for this claim are:
· Seeing others’ behavior activates a social proof heuristic, which states that in ambiguous situations, people will rely on the behavior of surrounding people and be influenced by it.
· People usually don’t want to contribute to a lost cause, and seeing others in the community making contributions will give the perception that that piece of content is ‘alive’ and perhaps useful to the group in some way. Related to this is the notion that people mostly don’t want to contribute when no one else is.
· People’s sense of fairness sometimes creates an obligation to contribute when they see that others have done so.
Harper  also conducted a study that showed that giving users information about the performance of other users increased their contribution in the short term. In that particular case the number of ratings (at a move site) were tracked, and people who had been emailed a newsletter containing comparisons with other people rated, on average, double the movies than people who’s newsletters didn’t have any comparison information.
|References|| Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics
and biases. Science, 185, 1124-1130
 Kraut, R. E., & Resnick, P. (In press). Encouraging online contributions to online communities. In R. E. Kraut, P. Resnick, S. Kiesler, J. Riedl, Y. Chen & J. Konstan (Eds.), Designing from theory: Using the social sciences as the basis for building online communities.
 Cialdini, R. B. (2001). Influence: Science and practice (4rd ed.). New York, NY, US: Allyn and Bacon.
 Wikipedia contributors, “The Wisdom of Crowds,” Wikipedia, The Free Encyclopedia, http://en.wikipedia.org/w/index.php?title=The_Wisdom_of_Crowds&oldid=315858186 (accessed October 9, 2009).
 Harper, F., Li, S., Chen, Y., & Konstan, J. (2007). Social comparisons to motivate contributions to an online community. Lecture Notes In Computer Science, 4744, 148. [OR]
I hope this is useful for you if you’re designing the social features of your site. Recommendations for improvements are welcome!