Social engagement drivers

This paper studies how online communities can foster social engagement. The study is carried out in a site for the neighbours of a suburban town, built in a Domino/Lotus environment. Three different aspects are examined: effects of several design element that were intended to increase interaction, users' profiles and subjects of the conversations.
Design
- while the site is structured in "rooms" for different topics, the "frontpage" (main room) concentrates activity and makes new material more visible
- others systems allow to track users' activities
- notification services
Members selection
Method: a survey has been sent to users in order to know their background and experience, general attitudes about the Internet and the site. The survey included 50 questions and covered different topics: attitudes about technology (comfort and skills, security, usage of synchronous and asynchronous skills), time use (hours spent working, unpaid work, leisure...). Several regression analysis have been carried out using the survey responses as independent variables and the logs of the site as dependent variables.

The independent variables used in the regression models were based on estimated factors scores, which where computed for each respondent using factors solutions.
The measure for participation (dependent variable) is the number of sessions.

While the method of research can be interesting, the outcomes are not surprising at all (we have to note that this text has been written in the turn of the century): skilled users are more likely to participate, as would do individual who spend a great deal of their non-work time socialising and in non-work Internet activities.

Content
The paper also study the subject of the longer threads of messages

Stimulating social engagement in a community network
by: David R Millen, John F Patterson

Filling one field with the value of another field

I am using the Biblio module for managing bibliographic references in a Drupal site and I found a problem when using views: these 2 modules are not integrated and when I require a one of its fields in a view I get code as plain text. Because of the first rush I used a trick to overcome the problem: making another field with CCK. Everytime an editor (myself) fill the form of a biblio, I need to copy an paste the content of 2 fields in another 2 extra (hidden) fields. I'm planning to make this available for a first bunch of end-users and obviously, this has to change.

One solution could be to remove this 2 extra hidden fields from the form and to fill them automatically using the default value field and a more consistent trick. Some hints to explore: http://drupal.org/node/260451

Gathering comments

When a feed is included to Friendfeed we can make comments to every post there. Therefore, we can have different threads of comments for the same post, one at the original blog and one at Friendfeed. If we use the FeedAPI module in Drupal we can make something similar as every post in an aggregated feed can become a node (this is the name for unit of content in Drupal) and thus being commented, tagged, rated...

Al this makes fragmented conversations. I read at RWW that some plug ins for Movable Type and Wordpress allow this applications to retrieve the comments that a post originated in one of these platforms has received at Friendfeed and include it in the comments thread. I've been searching but nothing like this seems to be available for Drupal.

Search patterns in a corporate social bookmarking service

This brilliant and useful paper found in Riina's blog explores the search patterns in dogear, a corporate social bookmarking service of a multinational company. This service, only available for company's employees, allows to bookmark internet and intranet links. Another particular feature of this system is the corportate identity of the employees that can not bet hidden by a pseudonym.

The research combines quantitative (log analysis of users actions, followed by cluster analysis of these data) and qualitative (15 interviews to users) methodology in order to explore search patterns within the dogear bookmarking. Three big groups are identificated: Community browsing, Personal search and Explicit search.

Millen, D., Yang, M., Whittaker, S., Feinberg, J., 2007. Social bookmarking and exploratory search
URL http://dx.doi.org/10.1007/978-1-84800-031-5\_2

The table (see above) shows the outcomes of the log analysis of users' actions where events represent the action of accessing a particular view (recent posts, another user bookmarks, oneself bookmarks...) and clicks the action of clicking in one result of these views.

Community search is the most common search pattern. Explicit search and personal search (oneself tags) come in second and third place. The more common pattern is to look at the recent post, but other strategies are also used, like looking at what "thought leaders" are bookmarking or what is hot in a particular topic. The interviews have highlighted that this strategies rely on the trust that employees have in the community or in some users. The fact that corporate identity (full name, contact details...) is displayed play an important role here, and also in another search pattern: looking for experts in the company.

Personal search states for users that come back to their own lists of bookmarks and tags. Users that make personal search are frequently those who are active bookmarkers.

While community search is typical of exploratory search (where the goal is not really to retrieve an element but to profile a user, a topic, news...), explicit search is more orientated to retrieve an element. This explains the high percentage of clicks (39%) in these views. Again, the trust in the community play an important role: "...relatively high proportion of clicks... combined with interviews comments suggest that social bookmarking services provide a good way to capture high value pointers to information sources".

Networks effects, some links

Dion Hinchliffe made a revision of the topic some time ago and explained that a project that want to exploit their potential need to foster it: "If you have a million people visiting your Web site but you're not leveraging network effects with them (such as by letting them contribute and letting others see and respond to those contributions), then you're probably squandering the greater part of the value of that million person audience."

There is also some links to the theories behind, Meltcalfe, Reed and Bob Briscoe, Andrew Odlyzko, and Benjamin Tilly.

Evolution of the percentage of edits made by active users in Wikipedia

Power of the few vs. wisdom of the crowd: Wikipedia and the rise of the bourgeoisie has used a history dump of English Wikipedia (58 millions of editions, 4,7 millions of pages). To process this data the have used a powerful environment based in Hadoop. The have calculated the number of edits made and the changes in content between edits (counting words, not lines). Users has also been classified by number of edits, and the editions have been grouped by types of users (from very active to sporadic).

Comparing Wikipedia coverage by domain areas

An Analysis of Topical Coverage of Wikipedia uses a random sample of 3000 articles. These articles have been classified by subjects. The extend of each article has been measured by the size of HTML page in kilobytes. The number of edits for every page has also been recorded.