This is the Post-print version of the Article. The official Published version can be accessed from the link below - Copyright @ 2012 IEEEWikipedia is the largest online service storing user-generated content. Its pages are open to anyone for addition, deletion and modifications, and the effort of contributors is recorded and can be tracked in time. Although potentially the Wikipedia web content could exhibit unbounded growth, it is still not clear whether the effort
of developers and the output generated are actually following patterns of continuous growth. It is also not clear how the users access such content, and if recurring patterns of usage are detectable showing how the Wikipedia content typically is viewed by interested readers. Using the category of Wikipedia as macro-agglomerates, this study reveals that Wikipedia categories face a decreasing growth trend over time, after an initial, exponential phase of development. On the other hand the study demonstrates that
the number of views to the pages within the categories follow a linear, unbounded growth.
The link between software usefulness and the need for software maintenance over time has been established by Lehman and other; the link betweenWikipedia usage and changes to the content, unlike software, appear to follow a two-phase evolution of production followed by consumption.This study is partly funded by the University of East London

Boldyreff, C

Capiluppi, A

Duarte Pimentel, A

English

Brunel University Research Archive

Patterns of Creation and Usage in the Evolution of WikipediaAna Claudia Duarte PimentelACE – University of East LondonLondon, UKu0914698@uel.ac.ukAndrea CapiluppiDISC – Brunel UniversityLondon, UKandrea.capiluppi@brunel.ac.ukCornelia BoldyreffACE – University of East LondonLondon, UKc.boldyreff@uel.ac.ukAbstract—Wikipedia is the largest online service storinguser-generated content: its pages are open to anyone for addi-tion, deletion and modifications, and the effort of contributorsis recorded and can be tracked in time.Although potentially the Wikipedia web content could faceunbounded growth, it is still not clear whether the effort ofdevelopers and the output generated are actually followingpatterns of continuous growth. It is also not clear how theusers access such content, or if recurring patterns are detectedin how the Wikipedia content is viewed by interested readers.Using the category of Wikipedia as macro-agglomerates, thisstudy reveals that also Wikipedia categories face a decreasingtrend, after an initial, exponential phase of development. Onthe other hand we also demonstrate that the number of viewsto the pages within the categories follow a linear, unboundedgrowth.I. INTRODUCTIONAn initial model of Wikipedia growth proposed in 2003predicted exponential growth of content, but when it be-came clear in 2007 that content growth was no longerexponential, a revised model of logistic, S-type growthwas found to more accurately reflect the actual growth ofWikipedia content [6], [4], [3]. In recent research on user-generated web content [1], Wikipedia pages in the categoryof ”Software Engineering” were found to follow a similarpattern of evolution to active Open Source Projects onSourceForge; they exhibited a slow growth rate followed byfaster growth and finally a decrease in growth. Even withthese additional results, it is still unclear how wide-spread isthis pattern, or whether a declining “production” of contentalso corresponds to a decreasing of “consumption” by users.This study analyses the evolution of a selection ofWikipedia pages and their categories, with two objectives:first, to demonstrate that different categories of pages inWikipedia show a similar pattern of evolution in both thenumber of contributors (who spend effort in creating orupdating the pages) and the resulting output, in terms ofnumber of edits. Second, to show that the level of consump-tion of the Wikipedia web content, measured via the pageviews by interested readers, is structurally different from theevolution of effort and edits, and it also evolves differently.II. RESEARCH DESIGNThis research was drawn around the Goal-Question-Metrics approach, that is, using “metrics” to assess somespecified “questions” to achieve an overall “goal”. The maingoal of this research is to extract recurring patterns ofevolution of Wikipedia pages when grouped by categories.The following questions were formulated for the evalua-tion of the above goal:1) Do Wikipedia categories generally exhibit the samepatterns of number of contributors over time?2) Do Wikipedia categories generally exhibit the samepatterns of number of edits over time?3) Do Wikipedia categories generally exhibit exhibit thesame patterns of number of views over time?The following metrics were used in the assessment of theabove questions:1) The effort of contributors was evaluated by countingthe number of unique (or distinct, in a SQL-liketerminology) contributors during a specific interval oftime. The chosen granularity of time was based onmonths (as “effort” in man-months [2]). In particular,we evaluated the number of unique (i.e., “distinct”)contributors per month, and also the cumulated num-ber of contributors, evaluated by summing up, formonth m, all the previous contributors up to monthm− 1 and the unique new contributors in month m.2) The work produced was evaluated by counting thenumber of edits to the Wikipedia pages during thesame intervals of time (i.e., monthly). Each Wikipediaedit is recorded with a plain-text description that isavailable to download via a dedicated web-page, asdetailed below. In particular, for every month m,we evaluated the number of edits that are performedon each category during m, and also the cumulatednumber of edits, summing up the edits of month mwith all the edits up to month m− 1.3) The number of views that each page is accessed byreaders was measured monthly to summarise whetherthe analysed pages and relative categories providevalue to the users. As an aggregate, we evaluated (forevery month m) both the monthly number of views ofall the pages in a category, and the cumulated numberof the views for the whole category up to month m.III. EMPIRICAL APPROACHIn order to select the categories to be studied for thiswork, as mentioned we selected a generic “Arts” domainwithin Wikipedia, and some of its associated categories:Architecture, Arts, Dance, Design, Fashion, Films, Painting,Photography, Sports and Theatre. Each Wikipedia categorylists many pages and subcategories, each containing severalhundreds of sub-pages. Since in Wikipedia the sub-pages arelabeled also with the main category (apart from their subcat-egory), all the pages from the categories and subcategorieswere considered to carry out this study.Table I summarizes the main characteristics of the studiedcategories, as per the latest month considered (April 2012):for example, the first row shows that the Architecturecategory is composed of 1,973 pages, it had 50,000 uniquecontributors so far, and its pages were added, changed oredited some 550,000 times. Finally, the last column showsthe amount of cumulative views that the pages in thecategory benefited since the earliest available date to thelatest month considered (330 million views).Category Pages Contributors Edits ViewsArchitecture 1,973 50k 550k 330MArts 855 26k 215k 265MDance 592 12k 153k 89MDesign 1,477 30k 250k 305MFashion 554 31k 287k 367MFilms 1,227 25k 280k 380MPainting 468 26k 240k 54MPhotography 675 23k 187k 295MSports 1,098 20k 206k 133MTheatre 985 17k 147k 140MTable ICHARACTERISTICS OF THE CHOSEN CATEGORIES (AS OF APRIL 2012)In order to analyse the Wikipedia pages, two Open Sourcetools were used:• Mediawiki Special:Export Interface: this interface1 al-lows a researcher to extract an XML file containing allthe revisions of a page (or a category of pages), foroffline analysis.• Mediawiki Dumper: this tool produces a SQL dumpfrom the previously downloaded XML dump2. Threetables were studied further: the “revision” table con-taining all the revision histories with timestamps; the“page” table containing the titles and the IDs of eachpage; the “text” table containing the whole text revi-sions as BLOB objects.A. ToolchainAn overview of the toolchain is visualized below (Fig-ure 1): the coloured items identify code that had to be1http://www.mediawiki.org/wiki/Manual:Parameters to Special:Export2http://svn.wikimedia.org/svnroot/mediawiki/trunk/mwdumper/written to join the inputs or the outputs of the available tools.After choosing a Wikipedia category at the top of the figure,scripts were generated to screen-scrape not only the pagesand the sub-categories contained in the chosen category,but also the sub-pages contained in the sub-categories. Withthe generated list of pages, a request was issued for everymonth and every page to the JSON server3 recording thepage views: it should be noted that, for all the categories,the earliest data on views available on JSON is Dec 2007.Such raw data had to be collected per page and aggregated,monthly, at the category level.Figure 1. Toolchain usedOn the other hand, a POST request was automatically sentto the Special:Export MediaWiki interface, to download therevision histories of the pages and the sub-pages composingthe analysed categories: it should also be noted that theMediaWiki interface allows to download only the first 1,000revisions for each page4. In many cases, the Wikipedia pageshave more than 1,000 revisions: for these pages, the latestreturned edit and time-stamp were noted, and other POSTrequests were issued staring from the time-stamp, in orderto download all the remaining revisions, in batches of 1,000.The data of both the views and the edits and contributorswas stored in a SQL storage and queries formulated toextract the metrics mentioned above.IV. RESULTS – EDITS AND CONTRIBUTORSIn this section we outline the results of our experiments,showing the the monthly and cumulative number of edits,and the monthly and cumulative number of unique contribu-tors, for the 10 categories studied. For reasons of space only3http://stats.grok.se/json/4The output revisions are the earliest ones, i.e., starting from revision 1.two categories are reported below, “Dance” and “Fashion”:most of the patterns apply to all the analysed categories.Figure 2 shows the cumulative number of edits as a dashedline, and the number of monthly edits as a continuous line,for both categories (“Dance” in Figure 2 top , and “Fashion”in Figure 2 bottom). The monthly number of edits in bothreported categories has a very long initial tail, a sharpincrease and a peak, after which the trend starts to decline:similar trends can be found in all of the studied categories.On the other hand, the cumulative number of edits seemsfollowing an S-shape, logistic curve: after a slow start, alarge increase in number of edits has now given way toa slower trend of addition and change of content. For theWikipedia at large, this result has been shown already [5],but our results show that smaller-level agglomerates sharethe same issue.Figure 2. Monthly and cumulated number of edits for two categoriesThe patterns observed above for the “edits” are also de-tected when plotting the number of contributors: in Figure 3the two selected categories are studied in depth again withrespect to contributors. A peak can also be seen in thedistribution of monthly contributors, which later declines tomuch smaller values.When fitting a regression model to these trends, we foundthat an exponential curve (up to the major peak) provides agood fit, but only considering the data up to the peak: in allthe categories, and for both the edits and contributors trends,the coefficient R2 reaches over 90% for the regression lines,as an indicator of the goodness of fit.The second part of these curves (which normally startsbetween 2007 and 2008) is instead a descending linearregression, with the R2 coefficients around 70% − 80%.Whether this second trend is irreversibly declining, and thenumber of contributors is destined to decline even further,are questions that need more data in the future months.Figure 3. Monthly and cumulated number of contributorsV. RESULTS – VIEWSThe results for the monthly and the cumulated number ofviews for the two categories described above is displayed inFigure 4. As mentioned above, the available data only startsfrom Dec 2007 onwards, i.e., around the time of the majorpeaks in the evolutionary trends of edits and contributors.The plots below show that the number of views in the twocategories, and in general for all the 10 categories studied,is increasingly monthly, and it has a very good linear fit atthe cumulative level (R2 over 99% in all the cases).Summarizing the results on edits, contributors and views,each category shows at the aggregate level a declining phaseof contributors’ effort and edits, and an increasing trend interms of views in the same periods. In the next sectionwe discuss this result in the context of production andconsumption of user-generated content.VI. DISCUSSION AND IMPLICATIONSLarge collections of related Wikipedia pages show similartrends in the number of the overall contributors who provideenhancements to, or create new Wikipedia pages. As alsofound in other works, the number of contributors, perFigure 4. Monthly and cumulated number of page viewscategory, is rapidly decreasing to mark a logistic curve. Thisis also mirrored by the number of edits to the pages ofthe analysed categories: although single pages show a muchlarger number of edits, and a steady number of contributors,the overall categories see a general decline in the effortprovided and the output produced.In this work we found that the decrease in activity on theWikipedia pages, as also reported in other works, is onlyone side of the user-generated content phenomenon: whentracking the number of views, the categories have a differenttrend from the “consumers” point of view, i.e. the usersof such content. After an exponential-driven growth trendof development and refinement (between 2001 and 2007for most categories), the effort and the work produced inthe Wikipedia categories have turned to linear, descendingtrends. This second descending trend is paired to an ascend-ing linear trend in the number of views, indicating that thepages and categories of Wikipedia have become a reliablesource of reference.Such user-generated content conforms to a two-phase evo-lution framework: in the “production” phase, the Wikipediacontent is massively generated and optimized; in the “con-sumption” phase, even if the activity of production declines,the knowledge becomes widely available and accessed by theconsumers who can establish, with their increasing views,such knowledge as an established and credible source ofinformation.VII. CONCLUSIONThis paper presented a quantitative analysis of 10 relatedcategories of Wikipedia pages, developed and evolved onlineby a large number of contributors. We observed two typesof results: first, at the aggregated level of categories, itis possible not only to confirm that also the Wikipediacategories are experiencing a slow-down in terms of activity,and the relative effort; it is also possible to divide theevolution of such online content into two trunks, a firstexponential phase of development, and a second, linearlydeclining, phase where less contributors and activity aredetected. Whether such descending trends will ever cometo a null activity has still to be confirmed by continuouslymonitoring the activity on the pages.The second result is still unreported in the literature: weshowed that the categories experience an increasing numberof views by interested readers. This trend is specular to the“edits” and “contributors” trends: although the productionof content has slowed down, the request of such knowledgeis increasing, which poses the foundation for a two-phaseframework of user-generated content.ACKNOWLEDGMENTThe authors would like to acknowledge support receivedfrom the University of East London who have fundedAna Claudia Duarte Pimentels participation in this researchunder its Undergraduate Research Internship Scheme 2012.The authors would also like to acknowledge the ErasmusResearch Interns, Giovanni M. Alluvatti, Giuseppe De Ruvoand Marco Molfetta, who worked with Dr Capiluppi duringSpring and Summer 2011 and contributed to the develop-ment of some of the tools used in this research.REFERENCES[1] G. M. Alluvatti, A. Capiluppi, G. De Ruvo, and M. Molfetta.User generated (web) content: trash or treasure. In Proc of12th Intl Workshop on Principles of Software Evolution and7th Annual ERCIM Workshop on Software Evolution, IWPSE-EVOL ’11, pages 81–90, New York, NY, USA, 2011. ACM.[2] F. P. Brooks, Jr. The mythical man-month (anniversary ed.).Addison-Wesley Longman Publishing Co., Inc., Boston, MA,USA, 1995.[3] S. T. K. Lam and J. Riedl. The Past, Present, and Future ofWikipedia. Computer, 44:87–90, March 2011.[4] F. Ortega. Wikipedia: A quantitative analysis. PhD thesis,Universidad Rey Juan Carlos – Escuela Te´cnica Superior DeIngenierı´a De Telecomunicacio´n, 2009.[5] B. Suh, G. Convertino, E. H. Chi, and P. Pirolli. The singularityis not near: slowing growth of Wikipedia. In WikiSym ’09: Procof the 5th Intl Symposium on Wikis and Open Collaboration,pages 1–10, New York, NY, USA, 2009. ACM.[6] J. Voss. Measuring Wikipedia. In Proc of 10th InternationalConference of the International Society for Scientometrics andInformetrics, Stockholm (Sweden), July 2005.

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