CZ:Statistics

Since its inception (Nov. 2006) and official launch (March 28, 2007), the Citizendium has grown. This page provides statistics on the Citizendium's output of articles and its contributor base. Our meta-discussions take place on the forum, the relevant statistics page is here.

Pages

Number of articles and pages

The first graph shows the number of articles (technically speaking, all pages from mainspace, without redirects and subpages), including articles that are not "live."

Fig. 1. Number of articles

The second graph shows number of all pages from all namespaces (e.g. userpages, talk pages and images are included, redirects are _not_). This is the green line. The blue line is the one from the first graph (i.e. the mainspace pages). What made the greeen line jump almost vertically mid February 2007? It was Saint Valentine's, when after slashdotting many new users registered and were welcomed on their talk pages. Notice that at the same time there was no parallel growth in the mainspace. Apparently, the newly registered users were mainly watching, since at that time there was no unregistered access. A more stable growth rate has been established after the launch.

Fig. 2. Number of all pages from all namespaces (green) and articles (blue).

Rate of article and page creation

The third and fourth figure present global creation rate. It measures the activity on the wiki expressed in new pages per day. The rate for "pure" articles (technically: mainspace without redirects) is depicted in blue; the green line corresponds to all pages (still, without redirects). This is calculated as the number of articles (pages, respectively) divided by the number of working days from the beginning. Obviously, this is a "global average", to be compared with a recent creation rate on the 5th graph of this section. It represents the creation rate for articles taking into account last 30 days only.

Fig. 3. Creation rate (articles per day)

Fig. 4. Overall creation rate in pages per day (green line); the blue line corresponds to articles' creation rate

Figure 5 indicates perhaps a more interesting statistic: recent creation rate. But it needs special explanation. In the earliest months of the project, the Citizendium was a "fork" of Wikipedia, i.e., we had uploaded all Wikipedia articles. Then, in mid-January 2007, the project's participants decided to "unfork," that is to delete all articles that were not tagged "live" i.e. improved or meant to be improved soon here on CZ. If an article appears to be created before that moment it means that it survived the "Big Unfork" procedure and the 'creation' date is in fact that of its first revision on CZ. In other words, the growing rate before mid-January is not very meaningful as the rules then were different and putting a tag or just correcting a typo 'created' an article. In the mid-January the article creation statistic plummeted to four articles per day--which was probably a better indicator of the rate at which we were creating our own new content.

There was a spike in February 2007 because of a self-registration period and then again in April-May 2007 because of our public launch and the accompanying publicity. There was a spike in November 2007 for three reasons: a press release, a "Stub Week" initiative, and (especially) a very broadly-distributed call for participation made to persons with unused Citizendium accounts. December 2007 experienced a relative lull no doubt largely on account of the holidays.

Fig. 5. Recent creation rate (last 30 day counted)

Edits daily

The number of edits is highly variable from one day to another and the graph of the actual data is hardly readable. More meaningful is the 30 days moving average depicted below. Trends are easily visible. The price for readability is a little shift from the actual events: the changes on graph appear a few days after it happened. For example the impact of the launch that occurred in March 2007 can be observed here a bit later. The graph takes into account edits in all namespaces.

Fig. 5a. Edits by day, 30 days moving average.

Human resources

Number of authors

The following graphs describe the CZ human resources. These graphs need clarification, because in the months leading up to February 2006, all new authors had to create their own bios, and very many new people did that and then nothing else. The Jan.-Feb. 2006 spike is due to a two-week period in which we allowed self-registration. There was also a spike that lasted from the end of March through May 2006, which corresponded to our public launch and the PR blitz that followed. The numbers from June 2006 on are perhaps a better indicator of long-term personnel trends on the wiki.

• How many authors are active each month? The Fig. 6 presents the number of users that made at least one edit (separately for each month).

Fig. 6. Editing authors

• How many users get more involved? Fig. 7. shows how many authors make at least 20 (at least 100, resp.) edits per month.

Fig. 7. Active authors

Daily contributors

How many contributors could you meet here daily, on average? While correlated with other human resources measures, this one seems to be interesting since it shows how many people make the community on a daily basis. See the figure below.

Fig. 8. Authors daily

New arrivals

Fig. 9: How many new authors arrive each month? This can be measured by counting new user pages. More substantial metric would be, however, to detect a new user on his first edit. Notice that in the period of self-registration (essentially, one week in January and two weeks in February 2007) the two metric largely coincide, as the new users were supposed to provide their bio. There was also a spike in March, which continued into April, due to our launch. New arrivals have been almost exclusively the result of press coverage, of which there has been relatively little over the summer, since our public launch. There were also fewer arrivals in the summer, probably due to the lower amount of academic activity generally.

Fig. 9. New arrivals

Comparison to other wikis

How does the statistical data shed light on Citizendium's strength in terms of human resources? Since April 2007 is the first month after the wiki's official launch, it is instructive to compare Citizendium with several active projects to similar size and mission. In the chart below, Citizendium is compared to several language Wikipedias. This analysis counts the registered users of each site.

Fig. 10. CZ - WP human resources comparison

As of April 2007, the human resources of CZ are comparable to resources of these Wikipedias from the category "more than 25,000 entries" . For example, CZ would be of the same order of magnitude as hr.wikipedia.org, lt.wikipedia.org, sl.wikipedia.org (these were slightly smaller) or sr.wikipedia.org (this one was a bit bigger than CZ). As a sidenote, there were not many active IP anons on these wikis (about 10; not counted here), roughly as many as robots (here, taken into account). Notice also that there were 24 Wikipedias altogether in the categories "more than 50000", "more than 100000" and "more than 250000" entries.

Word count

The table below is based on database dumps made about the end of every month. The following example explains its content.

As of end of July, 2007, Citizendium contained about 4100K words in its articles. We do not count the tables, nor "infoboxes". Technical information, as e.g. categories or http links are not counted. Draft pages are excluded. A typical article was about 562 words long. In fact, this is the median size, which means that, at the time, half of our articles were longer. There were about 3170 clusters.

A cluster means here the main article with a set of subpages describing given subject (this is the basic unit of Citizendium). The difference between the numbers shown here and the 17,697 total articles displayed on the Welcome Page is that the latter count includes neither external articles nor articles without metadata (which are typically lemma articles, i.e. containing just a short definition or description of the subject). Note also that for computing the median size only the main (or base) page of each cluster (without any subpages) is taken into account.

Date	Total Words	Words per day	Clusters	Cluster increase	Median length in words
July, 2007	4100K	N/A	3170	N/A	562
August, 2007	4415K	10.5K	3480	300	551
September, 2007	4577K	5.4K	3771	301	511
October, 2007	4889K	10.4K	4200	429	468
November, 2007	5297K	13.6K	5092	892	385
December, 2007	5603K	10.2K	5493	401	369
January, 2008	5914K	10.4K	6005	512	350
February, 2008	6165K	8.4K	6334	329	344
March, 2008	6484K	10.7K	6681	347	339
April, 2008	6963K	16K	7126	445	339
May, 2008	7744K	26K	7716	590	340
June, 2008	8042K	9.9K	8185	465	323
July, 2008	8375K	11.1K	8711	526	319
August, 2008	8708K	11.1K	9238	527	315
September, 2008	8930K	7.4K	9673	435	308
October, 2008	9120K	6.3K	10042	369	301
November, 2008	9370K	8.3K	10543	501	291
December, 2008	9589K	7.3K	11007	464	283
January, 2009	9748K	5.3K	11239	232	283
February, 2009	9878K	4.3K	11628	389	275
March, 2009	10044K	5.5K	12035	407	265
April, 2009	10218K	5.8K	12265	230	266
May, 2009	10540K	10.7K	12706	441	264
June, 2009	10677K	4.6K	13137	431	258
July, 2009	10998K	10.7K	13789	652	245
August, 2009	11238K	8K	14617	828	232
September, 2009	11513K	9.2K	15176	559	224
October, 2009	11730K	7.2K	15882	706	213
November, 2009	11887K	5.2K	16687	805	198
December, 2009	12013K	4.2K	17072	385	193
January, 2010	12140K	4.2K	17750	678	184
February, 2010	12286K	4.9K	18303	553	176
March, 2010	12517K	7.7K	18994	691	169
April, 2010	12684K	5.6K	20036	1042	155

Structure of articles and workgroups

Checklisted articles

Recall that we categorize the articles as follows

• External (imported and not yet improved)
• Stubs (no more than few sentences)
• Developing (beyond a stub but incomplete)
• Developed (complete or nearly so)
• Approved (that's it!)

Structure of articles.

And this is, approximately, how it evolved in time.

Articles by workgroup

Articles by workgroups

...and how it came to this

Members by workgroup

Authors

Registered editors

Progress in time

Here we graph the number of articles in various workgroups vs. time.