With the promotion to featured article (FA) of Grus (constellation) on 17 May, Casliber became Wikipedia's second featured-article centurion, following Wehwalt's groundbreaking achievement last December. Cas's first FA, Banksia integrifolia, a group effort, was promoted on 16 November 2006. His first solo project, Diplodocus, followed in January 2007; he has rarely been off the FAC page since. Quite apart from his regular and meticulous content work, Cas has contributed to many other aspects of the Wikipedia project – I'm always seeing his name, contributing, helping, leading. I caught up with him recently, and he graciously agreed to answer a few of my questions.
First, many congratulations on achieving the rare feat of 100 featured articles, an awesome accomplishment. Without wishing to breach your anonymity, can you reveal a little bit about yourself?
When did you begin editing WP, and what brought you here in the first place?
Yes, I've been studying your featured article log; a fascinating medley: the predominant subjects are flora, fauna and (more recently) constellations, but occasionally, oddities turn up – a dinosaur, a novel (The Historian), a medical article. You clearly have a wide panorama of interests; do you have any specific method for choosing your subjects, or, like me, do you tend to follow your instincts?
I see you mentioned Wadewitz there, sadly no longer with us – I, too, enjoyed working with her in my early WP years. We never formally co-produced an article, though we talked of it from time to time. Are there other editors who particularly helped you in your early days, that you'd like to acknowledge now?
I started a year or so after you, and I think FAC has changed a lot since then. I think standards have risen considerably – it takes me far longer than it used to to put an FA together. What differences in the FAC procedure have you experienced? Do you agree that FA standards have risen?
Now, writing featured content is only a part of your overall WP contribution. You are an active reviewer, an admin, you've been an arbcom and, of course, you are the prime mover behind the annual core contest (which I've been happy to judge from time to time). Which of these various roles have you found most rewarding?
How do you see your contribution to WP over the next few years? More generally, how do you see Wikipedia developing? Are there any basic changes that you would like to see implemented?
Well, I see that you have plenty of ideas, and it is refreshing to see someone who has kept their enthusiasm and is still thinking ahead. It has been a pleasure to talk to you, Cas, and I'm sure all your fellow editors join me in hoping that we'll see and hear plenty more from you in the future.
100. Grus (constellation) |
Howard G. ("Ward") Cunningham, who turned 65 last week, has special distinction in these realms as the developer of the first wiki. An American computer programmer, his profound innovation was first installed on the Internet in March 1995. Cunningham remains a dynamic professional force: after a career in the corporate sector, since 2011 he has been "Co-Creation Czar" for CitizenGlobal, an innovative video and photo crowdsourcing platform that enables organizations to easily collect and analyze eyewitness media and data. He is also Nike's first Code for a Better World Fellow.
One of Cunningham's memorable quips is: "the best way to get the right answer on the Internet is not to ask a question, it's to post the wrong answer," which has come to be known as Cunningham's law. Its author is reported to have said: "Wikipedia may be the most well-known demonstration of this law."
As part of his birthday celebrations, WMF's Victor Grigas published an interview with Cunningham originally recorded in 2011. The following quotes are drawn from the significant statements he makes in the video:
“ | There’s a couple of things that Wikipedia did right, that didn’t even occur to me – for example, getting the licensing right. I was careless about licensing and I think that saying: "this has to be the licensed this way, here’s the ownership, here’s the guarantees going forward” is important, and I just wasn't interested in that stuff, so I just didn’t do that right. … I was open, but there was no guarantee that [the licensing] was open. There was no agreement when somebody submitted – there was an expectation, but it wasn’t written down. And in fact I think when I finally did write it down, it said, "I own it, you have the right to use it, but you can’t keep it." – and that’s not really open. But I think Jimmy Wales’ relationship to [software freedom activist] Richard Stallman got that right. The other thing ... I thought would be too hard [for a wiki] was being international. ... that international aspect is profound, in terms of having the opportunity of bringing the world together, Wikipedia is probably one of the strongest forces ... for creating peace in the world. That's fabulous, [that] it could be done in every language, when you find yourself reading an encyclopedia that is about the things you care about, because it was written by people just like you, talking about what they care about, and that caring becomes so important to you, you trust this. The fact that that same sort of interaction is happening in a lot of different cultures. ... it makes you part of one world – one world of ideas – and the idea that every language is important, just as every person is important.” |
” |
Seven featured articles were promoted this week.
For other featured article news, please see the accompanying Signpost report on Casliber becoming Wikipedia's second featured article centurion.
Three featured lists were promoted this week.
Four featured pictures were promoted this week.
In the US, Memorial Day marks the unofficial beginning of summer, and summer is definitely on people's minds this week, with summer films Godzilla and X-Men: Days of Future Past, the apparently designated summer song "Fancy" by Iggy Azalea, and summer TV show, Game of Thrones. The Indian general election is only fading slowly, understandably as its effects have yet to be fully felt.
For the full top 25 list, see WP:TOP25. See this section for an explanation for any exclusions.
For the week of May 18 to 24, the 10 most popular articles on Wikipedia, as determined from the report of the 5,000 most viewed pages, were:
Rank | Article | Class | Views | Image | Notes |
---|---|---|---|---|---|
1 | Mary Anning | 1,750,729 | She sells seashells by the seashore. She was Mary Anning, who not only found and sold fossil seashells but also identified the first ichthyosaur (at age 12!) and the first plesiosaur. A victim of the gender and class prejudice of her time, she didn't get the recognition she deserved until after her death; an oversight Wikipedia viewers have gone some way to correcting thanks to a birthday Google Doodle on 21 May. | ||
2 | Godzilla (2014 film) | 797,814 | It seems that Hollywood's trust in Gareth Edwards, director of the microbudget scifi flick Monsters, was well placed, as his take on the Godzilla mythos has emulated its eponymous hero, stomping the box office to dust with $93 million in three days. Critics seem to like the movie too; it's RT rating is currently 73%. Personally, I had issues with it, but then, what do I know? | ||
3 | Rubik's Cube | 766,499 | Nothing is more likely to generate Wikipedia views than an interactive Google Doodle, and to celebrate the 40th anniversary of the ingenious puzzle, Google effectively rendered it irrelevant by constructing a fully solvable virtual version and releasing it online for everyone to try. | ||
4 | Steve Wozniak | 733,241 | The co-founder of Apple Computer got a massive one-day spike on 18 May, the same day he published an open letter to the FCC demanding they retain net neutrality in the US. I'm usually suspicious of 1-day spikes with no tail-off, but this instance is at least explicable. | ||
5 | Amazon.com | 656,462 | This article suddenly reappeared in the top 25 after a long absence, but at least it has a reason: Amazon Fire TV; a digital streaming device to watch online content on a HDTV. How it distinguishes itself from the three or four other such devices currently on the market is a matter of some dispute. | ||
6 | Narendra Modi | 544,033 | Thanks to an effective ad campaign and a sound economic record as Chief Minister of the state of Gujarat, Modi led his Hindu nationalist BJP to victory with a stomping 282 (52%) seats. A Hindu nationalist and a member of the RSS, Modi is considered a controversial politician and debate still surrounds the extent of his role in the 2002 Gujarat riots during his tenure as Chief Minister. The Indian National Congress, the party that has mostly led India since its independence, came in second with 44 seats, its worst showing in any election in India's history. | ||
7 | Game of Thrones | 507,708 | New seasons of this immensely popular show always draw people to Wikipedia. | ||
8 | Memorial Day | 456,537 | The last Sunday in May (that's May 26 this year), the day that the United States chose to honour its war dead, is perhaps better known as the traditional beginning of US summer vacation, and is thus eagerly anticipated by millions of people too young to serve but old enough to stand in line for action movies. | ||
9 | Game of Thrones (season 4) | 455,733 | This is the page with the plot synopses for each episode. | ||
10 | Iggy Azalea | 432,512 | The Australian/American rapper released her debut album, The New Classic on 21 April, but probably re-entered the top list due to an earpiece malfunction during a performance of her single "Fancy" on Dancing With The Stars |
A monthly overview of recent academic research about Wikipedia and other Wikimedia projects, also published as the Wikimedia Research Newsletter.
This paper[1] is another major literature review of the field of Wikipedia studies, brought forward by the authors whose prior work on this topic, titled "The People’s Encyclopedia Under the Gaze of the Sages"[supp 1] was reviewed in this research report in 2012 ("A systematic review of the Wikipedia literature").
This time the authors focus on a fragment of the larger body of works about Wikipedia, analyzing 99 works published up to June 2011 on the theme of "Wikipedia readership" – in other words focusing on the theme "What do we know about people who read Wikipedia". The overview focuses less on demographic analysis (since little research has been done in that area), and more on perceptions of Wikipedia by surveyed groups of readers. Their findings include, among other things, a conclusion that "Studies have found that articles generally related to entertainment and sexuality top the list, covering over 40% of visits", and in more serious topics, it is a common source for health and legal information. They also find that "a very large number of academic in fact have quite positive, if nuanced, perceptions of Wikipedia’s value." They also observe that the most commonly studied group has been that of students, who offer a convenience sample. The authors finish by identifying a number of contradictory findings and topics in need of further research, and conclude that existing studies have likely overestimated the extent to which Wikipedia's readers are cautious about the site's credibility. Finally, the authors offer valuable thoughts in the "implications for the Wikipedia community" section, such suggesting "incorporating one or more of the algorithms for computational estimation of the reliability of Wikipedia articles that have been developed to help address credibility concerns", similar to the WikiTrust tool.
The authors also published a similar literature review paper summarizing research about the content of Wikipedia, which we hope to cover in the next issue of this research report.
A paper[2] presented at the WWW 2014 Companion Conference analyzes the readership patterns of the English and Chinese Wikipedias, with a focus on which types of articles are most popular in the English- or Chinese-language time zones. The authors used all Wikipedia pages which existed under the same name in both languages in the period from 1 June 2012 to 14 October 2012 for their study, coding them through the OpenCalais semantic analysis service with an estimated 2.6% error rate.
The authors find that readers of the English and Chinese Wikipedias from time-zones of high Chinese activity browse different categories of pages. Chinese readers visit English Wikipedia about Asian culture (in particular, Japanese and Korean pop culture) more often, as well as about mobile communications and networking technologies. The authors also find that pages in English are almost ten times as popular as those in Chinese (though their results are not identifying users by nationality directly, rather focusing on time zone analysis).
In this reviewer's opinion, the study suffers from major methodological problems that are serious enough to cast all the findings in doubt. Apparently because the authors were unaware of Interlanguage links and consider only articles which have the same name (URL) in both the English and Chinese Wikipedians, they find that only 7603 pages were eligible to be analyzed (as they had both an English and Chinese version), however the Chinese Wikipedia in the studied period had approximately half a million articles; and while many don't have English equivalents yet, to expect that less than 2% did seems rather dubious. Similarly, our own WikiProject China estimates that English Wikipedia has almost 50,000 China-related articles. That, given that WikiProject assessments are often underestimating the number of relevant topics, and usually don't cover many core topics, suggests that the study missed a vast majority of articles that exist in both languages. It is further unclear how English- and Chinese-language time-zones were operationalized. The authors do not reveal how, if at all, they controlled for the fact that readers of English Wikipedia can also come from countries where English is not a native language, and that there are hundreds of millions of people outside China who live in the five time zones that span China, which overlap with India, half of Russia, Korea and major parts of Southeast Asia. As such, the findings of that study can be more broadly interpreted as "readership patterns of English and Chinese Wikipedia in Asia and the the world, regarding a small subset of pages that exist on both English and Chinese Wikipedia."
Bipartite Editing Prediction in Wikipedia[3] is a paper wherein the authors aim to solve what they call the "link prediction problem". Essentially they aim to answer "which editors will edit which articles in the future." They claim the social utility of this is to suggest articles to edit to users. So in some ways this is a similar function to SuggestBot, but using different techniques.
Their approach here is to use a bipartite network modelling. A bipartite network is a network with two node-types, here editors and articles. Using bipartite network modelling is becoming increasingly trendy, like Jesus (2009)[supp 2] and Klein (2014).[supp 3]
Explaining their method, the researchers outline their two approaches: "supervised learning" and "community awareness". In the supervised learning approach the machine learning features used are Association Rule, K-nearest neighbor, and graph partitions. All these features, they state, can be inferred directly from the bipartite network. In the community awareness approach, the Stanford Network Analysis Project tool is used to cut the network into co-editor sets, and then go on to inspect what they call indirect features which are sum of neighbors, Jaccard coefficient, preferred attachment, and Adamic–Adar score.
The authors proceed to give a table of their results, and highlight their highest achieving precision, and recall statistics which are moderate and contained in the interval [.6, .8]. Thereafter a short non-interpretive one-paragraph discussion concludes the paper saying that these results might be useful. Unfortunately they are not of much use, since while they declare their sample size of 460,000 editor–article pairs from a category in a Wikipedia dump, they don't specify which category, or even which Wikipedia they are working on.
This machine learning paper lacks sufficient context or interpretation to be immediately valuable, despite the fact that they may be able to predict with close to 80% F-measure which article you might edit next. Therefore the paper is a good example of the extent to use Wikipedia for research without even feigning attempt to make the research useful to the Wikipedia community, or even frame it in that way.
A list of other recent publications that could not be covered in time for this issue – contributions are always welcome for reviewing or summarizing newly published research.
{{cite journal}}
: Cite journal requires |journal=
(help)