While the world was watching fireworks displays in celebration of the 2018 New Year, the English Wikipedia's editing community was experiencing a different kind of fireworks: back-to-back topic bans and blocks, including a few that were considered controversial and involved tenured editors who have since retired. It gave new meaning to "Should Old Acquaintance be forgot, and never thought upon".
Discussions for two New Year’s resolutions resulted, focused on the blocking policy and block log redaction:
The issues revolve around the way editors treat each other and the manner in which administrators act as "first responders", particularly in situations when a tenured editor becomes the recipient of a controversial block or topic ban.
Edit warring, discretionary sanctions, ambiguity in policies and guidelines, a lack of consistency in administrator actions, concerns over the unfettered use of admin tools, bad judgment calls, biases, human error, anger and frustration are, while not the norm, major pitfalls in editor retention. Blocks and topic bans are intended as remedial actions to stop disruption but at times tend to appear punitive and magisterial, which exacerbates the situation and raises doubt as to whether the end truly does justify the means, particularly when such actions arise from misunderstandings and misinterpretations.
It's natural for editors to defend against a block or ban – to feel angry when they believe a situation was punitive or grossly mishandled. It is also equally as natural for an admin to maintain an opposing view by defending their actions by insisting (and believing) it was neither punitive nor mishandled. An admin's primary concern is to stop disruption and prevent harm to the project. When the dust settles, what usually remains is the user's block log, but what does that log actually tell us?
Controversial topics germinate disruption, and when POV warriors and/or advocacies are involved, content disputes are likely to end in topic bans and/or blocks. Wikipedia doesn’t have content administrators, rather we have what some editors refer to, with levity, as behavior police. Editors also have access to a number of specialized notice boards for discussion, but some are considered nothing more than extensions of the article TP in that the same editors are involved in the discussions. Add discretionary sanctions to the mix, including stacked sanctions that add confusion and make it difficult to interpret their intent or application, and what we end up with are sanctions that act more like a repellent than a preventative...well, perhaps one could consider it a preventative if it repels but that should not be the ultimate goal.
The thought of being "blocked" or "topic banned" is unsettling whereas the action itself can be quite demoralizing, and at the very least, a disincentive. The term dramah board, in and of itself, speaks volumes as an area to avoid. Perhaps we should consider replacing the block-ban terminology in the log summaries with less harsh descriptions like "content dispute, 24 hr time-out", or "30-day wikibreak – conduct time-out". The harmful effects of blocks and topic bans are also evident in editor retention research, as are the inconsistencies in admin actions across the board. While the blocking policy provides guidance, admins are still dealing with individual judgment calls and unfettered use of the mop, both of which conflict with the stability of consistency.
Questionable blocks and errors are often attributable to time constraints, work overload, inexperience, miscommunication, and misinterpretations. Other blocks of concern, although extremely rare, may be the result of POV railroading, ill-will, biases or COI, situations which are usually remedied with expediency, and may result in desysopping. Unfortunately, bad blocks remain permanently on the logs.
Another unfortunate consequence of block logs involves the adaptation of preconceived notions and bad first impressions after review, which may lead to users being wrongfully "branded" or "targeted", for lack of a better term, and possibly even rejected by the community. Block logs are readily accessible to the public, and include only the resulting block summary, not the circumstances which may persuade the reader to draw a much different conclusion.
Few, if any, actually care or are willing to invest the time to research the circumstances that led to a block; it's a difficult and time consuming task at best. Accepting the log at face value is much easier; therefore, in reality the block log is actually a rap sheet that is used to judge an editor’s suitability. Unfortunately, the right to be forgotten eludes us. Hopefully that will change.
26 featured articles were promoted.
Nine featured lists.
Five featured pictures were promoted.
A monthly overview of recent academic research about Wikipedia and other Wikimedia projects, also published as the Wikimedia Research Newsletter.
This paper by Chen et al.[1] proposes to use the Wikipedia article corpus as a source of world knowledge in order to answer open domain questions. They point out that Wikipedia articles contain a lot more information than current knowledge bases, such as DBPedia or Freebase. While knowledge in KBs is encoded in a more machine-friendly way, the vast majority of Wikipedia's knowledge is not covered in KBs, but contained in unstructured text and is thus difficult to access in an algorithmic way. The proposed approach, called "DrQA", aims to overcome that limitation by leveraging the article content. It first retrieves Wikipedia articles relevant to a question, and then uses a recurrent neural network (RNN) to detect relevant parts in the article's paragraphs that could be used as answers. This RNN is based on a set of pretrained word embeddings as well as a set of other features.
Their results indicate that DrQA seems better suited to answer open domain questions than other competitors, based on a set of four question benchmarks. While the evaluation score improvement seems rather small (77.3 vs 78.8 F1 score), the whole task of machine reading at scale using Wikipedia gives directions for interesting future research and applications. For example, depending on the speed of the framework (which unfortunately was not discussed), a new Wikipedia service for answering such open domain questions could be established. Furthermore, this process of answering common knowledge questions could help in improving chatbots.
This Carnegie Mellon University study[2] quantified the success of those editors who engage in talk page discussions and their roles in these discussions. The roles assigned to each editor was:
Unlike earlier studies exploring editor interactions, editors in this study could be assigned simultaneous roles on an article talk page. Success of each editor was determined by analyzing subsequent edits to the article under discussion which were promoted by a particular editor and longevity of these edits. Those editors that are more detail-oriented tend to have more success than those more interested in organization. Multiple editors assuming the role of organization lessens the success of individual editors. The study assessed 7,211 articles, 21,108 discussion threads, 21,108 editor discussion pairs, and the average number of editors per discussion. The number of total edits by an editor is not associated with success.
The researchers also published a dataset consisting of "53,175 instances in which an editor interacts with one or more other editors in a talk page discussion and achieves a measured influence on the associated article page".
This article[3] focuses on the 1.2 million unassessed articles in the Polish Wikipedia, and considers "over 100 linguistic features to determine the quality of Wikipedia articles in Polish language." From the conclusion: "Use of linguistic features is valuable for automatic determination of quality of Wikipedia article in Polish language. Better results in terms of precision can be achieved when the whole text of [an] article is taken into the account. Then our model shows over 93% classification precision using such features as relative number of unique nouns and verbs (unique, 3rd person, impersonal). However, if we take into account only [the] leading section of an article, relative quantity of common words, locatives, vocatives and third person words are the most significant for determination of quality. Using the obtained quality models we [assess] 500 000 randomly chosen unevaluated articles from Polish Wikipedia. According to result, about 4–5% of assessed articles can be considered by Wikipedia community as high quality articles."
See the research events page on Meta-wiki for upcoming conferences and events, including submission deadlines.
Other recent publications that could not be covered in time for this issue include the items listed below. contributions are always welcome for reviewing or summarizing newly published research.
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(help) The Wikimedia Foundation's Analytics team is releasing a monthly clickstream dataset. The dataset represents—in aggregate—how readers reach a Wikipedia article and navigate to the next. Previously published as a static release, this dataset is now available as a series of monthly data dumps for English, Russian, German, Spanish, and Japanese Wikipedias.
Have you ever looked up a Wikipedia article about your favorite TV show just to end up hours later reading on some obscure episode in medieval history? First, know that you're not the only person who's done this. Roughly one out of three Wikipedia readers look up a topic because of a mention in the media, and often get lost following whatever link their curiosity takes them to.
Aggregate data on how readers browse Wikipedia contents can provide priceless insights into the structure of free knowledge and how different topics relate to each other. It can help identify gaps in content coverage (do readers stop browsing when they can't find what they are looking for?) and help determine if the link structure of the largest online encyclopedia is optimally designed to support a learner's needs.
Perhaps the most obvious usage of this data is to find where Wikipedia gets its traffic from. Clickstream data can not only be used to confirm that most traffic to Wikipedia comes via search engines, it can also be analyzed to find out—at any given time—which topics were popular on social media that resulted in a large number of clicks to Wikipedia articles.
In 2015, we released a first snapshot of this data, aggregated from nearly 7 million page requests. A step-by-step introduction to this dataset, with several examples of analysis it can be used for, is in a blog post by Ellery Wulczyn, one of the authors of the original dataset.
Since this data was first made available, it has been reused in a growing body of scholarly research. Researchers have studied how Wikipedia content policies affect and bias reader navigation patterns (Lamprecht et al, 2015); how clickstream data can shed light on the topical distribution of a reading session (Rodi et al, 2017); how the links readers follow are shaped by article structure and link position (Dimitrov et al, 2016; Lamprecht et al, 2017); how to leverage this data to generate related article recommendations (Schwarzer et al, 2016), and how the overall link structure can be improved to better serve readers' needs (Paranjape et al, 2016).
Due to growing interest in this data, the Wikimedia Analytics team has worked towards the release of a regular series of clickstream data dumps, produced at monthly intervals, for 5 of the largest Wikipedia language editions (English, Russian, German, Spanish, and Japanese). This data is available monthly, starting from November 2017.
A quick look into the November 2017 data for English Wikipedia tells us it contains nearly 26 million distinct links, between over 4.4 million nodes (articles), for a total of more than 6.7 billion clicks. The distribution of distinct links by type (see Ellery's blog post for more details) is as follows:
If we build a graph where nodes are articles and edges are clicks between articles, it is interesting to observe that the global graph is strongly connected (157 nodes not connected to the main cluster). This means that between any two nodes on the graph (article or external entrypoint), a path exists between them. When looking at the subgraph of internal links, the number of disconnected components grows dramatically to almost 1.9 million forests, with a main cluster of 2.5M nodes. This difference is due to external links having very few source nodes connected to many article nodes. Removing external links allows us to focus on navigation within articles.
In this context, a large number of disconnected forests lends itself to many interpretations. If we assume that Wikipedia readers come to the site to read articles about just sports or politics but neither reader is interested in the other category we would expect two "forests". There will be few edges over from the "politics" forest to the "sports" one. The existence of 1.9 million forests could shed light on related areas of interest among readers – as well as articles that have lower link density – and topics that have a relatively small volume of traffic, making them appear as isolated nodes.
If you're interested in studying Wikipedia reader behavior and in using this dataset in your research, we encourage you to cite it via its DOI (doi.org/10.6084/m9.figshare.1305770) and to peruse its documentation. You may also be interested in additional datasets that Wikimedia Analytics publishes (such as article pageview data) or in navigation vectors learned from a corpus of Wikipedia readers' browsing sessions.
Joseph Allemandou, Senior Software Engineer, Analytics
Mikhail Popov, Data Analyst, Reading Product
Dario Taraborelli, Director, Head of Research
The Rambling Man has written the most featured lists of any Wikipedian. This interview dwells upon his editing process, and how he gets articles up to Featured List status.
This week's report is considerably more diverse, for better or worse. As ever, television has a dominant effect on the reading habits of Wikipedia's users, with Netflix maintaining its chokehold, securing eyes both on its own site and over here. The return of a pair of crime dramas also provided some intrigue for the readers of the wiki. The leading article, however, is that of Dolores O'Riordan, the lead singer of the Cranberries, who died tragically at a young age during the week. As ever, we can thank Reddit and Google for a couple of entries on the Report, and sports gasp also managed to make its way in, encroaching on the fiefdom of period drama fanatics. With the apparent addiction to television that is suffered by many a reader on Wikipedia, it is little wonder that we spend our time like zombies, clicking through tangentially related links. Long may it last, I say.
For the week of January 14 to 20, 2018, the most popular articles on Wikipedia, as determined from the WP:5000 report were:
Rank | Article | Class | Views | Image | Notes |
---|---|---|---|---|---|
1 | Dolores O'Riordan | ![]() |
2,536,032 | ![]() |
Beginning with musical tragedy, we have the death of the lead singer of The Cranberries (#4). This decade has had a remarkably high rate of attrition for talented musicians, and the death of my fellow countrywoman hit harder than most. From brave political statements to a oft-used ballad about rêves, the singer left a mark in her short life. Anyway, this is too upsetting to set the tone for the Report as a whole, so I shan't linger. |
2 | Martin Luther King Jr. | ![]() |
1,130,743 | ![]() |
The national holiday to celebrate the champion of civil rights fell this week stateside, as it does every year. Intrigue surrounding the pastor was likely piqued by the fact that many media outlets drew parallels between a holiday designed to mark the life and death of the man who vanquished segregation, and Donald Trump's vitriol and rhetoric. |
3 | Gianni Versace | ![]() |
1,051,793 | ![]() |
The legendary fashion designer is, perhaps not surprisingly, the subject of The Assassination of Gianni Versace: American Crime Story, the second season of American Crime Story. While the enterprise has not received the approval of Versace's family members, it seems to have riveted the readers of Wikipedia. If it can emulate the quality of its predecessor, we may perhaps truly understand why exactly the assassin (#5) decided to leave the icon on the floor. |
4 | The Cranberries | ![]() |
1,018,955 | ![]() |
The band lost their lead singer, Dolores O'Riordan (#1), following her untimely demise in London. This prompted an outpouring of wiki-emotion and interest in the group, propelling them to the top 5 for the week. |
5 | Andrew Cunanan | ![]() |
869,460 | ![]() |
The assassin of #3, Cunanan is also investigated thoroughly in the second season of American Crime Story, which seems to have propelled vast interest in his article. A notorious serial killer, Cunanan committed suicide following a lengthy and infamous manhunt. Unfortunately, should doubt persist about his guilt, we are in trouble. We cannot check if the glove fits, as he was cremated following his death. |
6 | Queen Victoria | ![]() |
782,363 | ![]() |
Another article which attracts constant attention from Anglophiles, Victoria is a staple of the report. She has seen her interest increase greatly as a result of the PBS and ITV series which bears her name, where she is portrayed by Jenna Coleman (pictured). Many consider it to be a poor man's crown, but it can't be denied that Wikipedia's users are captivated by period drama focused on British queens. |
7 | Deaths in 2018 | ![]() |
765,887 | ![]() |
Led by the demise of O'Riordan (#1), and a pioneering footballing legend, there was a lot of traffic at the list of the dead this week. Let's hope we are not in for another celebrity apocalypse. |
8 | Elizabeth II | ![]() |
735,840 | ![]() |
Once again, Elizabeth Regina makes her way onto the Report by virtue of The Crown. Having written extensively about the series due to the high presence of second screeners, I finally decided to indulge in the series and binge watched it in its entirety. On the whole, I found it to be very entertaining, and yes, found myself journeying to the pages of the characters in the period drama – am I part of the problem? |
9 | Schöningen Spears | ![]() |
641,099 | ![]() |
Another week, another Reddit entry sparking intense interest on Wikipedia. While I don't frequent r/TIL myself, I, as a commentator, do have to thank the moderators for introducing variety into the report. This one relates to wooden spears, which, through dendrochronology, have been dated as being over 300,000 years old. They were found very well preserved in a German mine. My question about this fascinating piece of trivia, naturally, given the fact that spears are potent weapons, is this – who had the bigger spear? On a side note, any of the TIL mods should journey over and help diversify DYK, as you clearly have the knack for it. |
10 | Case Keenum | ![]() |
612,896 | I have never understood why Minnesota of all places adopted the Vikings as their sporting idols. I mean, Miami Dolphins, I get. 49ers, sure. But why the Vikings? Because it is cold in Minneapolis? Because you enjoy historical anachronisms? Demographics indicate that it should be the Saxons. It truly puzzles me, as someone who stems from a Viking town. Nonetheless, Keenum's story this year has been remarkable, progressing from third-choice QB to a Super Bowl contender. The air will be let out of the balloon, though, when the Norse legions get wiped out by a ragtag volunteer army and their venerated general – or not. |
Feel like the report was pretty much the same from week to week? We've got you covered, as only four entries remain from the last report, the ever-present death list and the subjects of the TV shows Wikipedia readers seem to watch. Most of the changes are sports related: three entries in the build-up to Super Bowl LII, the possibility of another gridiron league returning, an association footballer making his debut, the two winners of the Australian Open, the latest UFC event... and on a darker, off-field note, two entries regarding the closure of a scandal akin to the Weinstein effect, as a pedophile physician who regularly abused American gymnasts is sent to prison. Also shifting things are three Google Doodles - that including the top two entries of the week - and a Reddit topic, four Indian entries (a new Bollywood epic, two historic figures depicted in it, and a national holiday), the Oscar nominations and the latest turmoil the US government has put itself into.
For the week of January 21 to 27, 2018, the most popular articles on Wikipedia, as determined from the WP:5000 report were:
Rank | Article | Class | Views | Image | Notes |
---|---|---|---|---|---|
1 | Virginia Woolf | ![]() |
1,497,132 | ![]() |
The feminist icon and author of, among other books, Mrs Dalloway received a Google Doodle celebrating her 126th birthday. |
2 | Sergei Eisenstein | ![]() |
1,169,678 | ![]() |
Like Virginia Woolf, pioneering Soviet filmmaker Eisenstein was born in the 19th century, peaked in the 1920s (including the iconic 1925 film Battleship Potemkin), died in the 1940s, and received a Google Doodle for his birthday (only this time a nice round number, 120). |
3 | USA Gymnastics sex abuse scandal | ![]() |
1,074,940 | ![]() |
In 2016, while it was revealed Russia was doping so many athletes to the point a whole slew of them were banned, another Olympics powerhouse saw a scandal that was as bad, if not worse: a former USA Gymnastics national team physician was denounced for sexually abusing over 150 athletes – including McKayla Maroney, seen to the left doing that famous "not impressed" face in illustrious company – since 1992. This week, said physician was sentenced to prison. |
4 | Tom Brady | ![]() |
980,001 | Unlike some of my friends, I don't care for American football. That being said, one of said friends is ecstatic that the Jacksonville Jaguars are incompetent and couldn't stop Brady and the New England Patriots from reaching a second consecutive Super Bowl and his eighth overall. | |
5 | Padmaavat | ![]() |
920,105 | ![]() |
India, ya know I love ya but baby you crazy. This week, a historic epic based on the poem Padmavat and starring Deepika Padukone (pictured) was released and is already making some big crore in spite of controversy – Padmaavat has been accused of being right wing and anti Muslim - that led to the movie being banned from a few Indian states, riots, firebombing, death threats to the director and cast, and even threats of mass suicide. |
6 | Republic Day (India) | ![]() |
832,560 | ![]() |
There. See? National holiday! Fun! Do that. Instead of threatening to murder people or set fire to things. Many Indians took it to watch the movie in our previous entry, despite increased security. |
7 | List of Super Bowl champions | ![]() |
766,992 | ![]() |
Self explanatory, really. Super Bowl LII is next week, and people wanted to remind themselves of the previous 51. The biggest winners are the Pittsburgh Steelers with six, though they can be matched by the New England Patriots if last year's result - seen in the picture, Tom Brady (#4) lifting the Vince Lombardi Trophy for the fifth time - repeats. Add the extended success to the fact that he's married to one of my country's most beautiful women and you can see why many downright envy Brady. |
8 | Deaths in 2018 | ![]() |
765,887 | ![]() |
Needs no introduction. And maybe the most notable death last week was Mort Walker, finishing off an impressive 68 years of writing Beetle Bailey. |
9 | Rani Padmini | ![]() |
730,645 | The legendary 13th–14th century Indian queen (Rani) who is the main character of Padmaavat (#5). | |
10 | 90th Academy Awards | ![]() |
711,802 | ![]() |
The latest Oscar contenders were announced by Andy Serkis and Tiffany Haddish (the latter, clearly struggling with the teleprompter), with the most nominated film being The Shape of Water (#13) amid the expected (most nominees, including Academy regulars Daniel Day-Lewis, Denzel Washington, and Meryl Streep) and surprises both good (Get Out for Best Picture! Logan for Best Adapted Screenplay!) and bad (The Boss Baby?!). The ceremony is on March 4th. |
Wikipedia is a powerful public health knowledge-translation tool. Across all languages, medical-related Wikipedia articles receive over 10 million visits per day from around the world.[1] To improve the quality of health-related Wikipedia articles, the Cochrane-Wikipedia Initiative was developed in 2014. Presently, there are over 2000 uses of Cochrane Reviews in Wikipedia. Many Cochrane Groups are training Wikipedia editors and developing new ways to share high-quality evidence on Wikipedia. Wiley and the Cochrane Library have distributed over 85 free accounts to Wikipedians to support the sharing of Cochrane evidence on Wikipedia.
Cochrane is a global non-governmental organization that works with a network of contributors from around the world. These collaborative teams produce Cochrane Reviews, a high-quality source of health-related information. Cochrane Reviews help people make informed decisions about treatment options by providing a summary of the best evidence in the field. Cochrane Reviews are peer-reviewed, credible, and unbiased (Cochrane does not accept funding from commercial sponsors or other potential conflicts of interest, for example). Cochrane Reviews meet Wikipedia’s reliable sources for medical articles criteria WP:MEDRS.
Many content errors in Wikipedia articles are due to not enough skilled editors inserting new evidence.[2] A new Cochrane project is tackling this! We have created a Wikipedia project page that includes a list of all the Cochrane Reviews not presently in Wikipedia. Volunteers will be directed to the project page, given Wikipedia-editing support, and encouraged to “be bold” (Wikipedia-style) and select Cochrane Reviews to insert into Wikipedia. There are over 5000 reviews on the list, and while not all of the reviews will have an obvious home in Wikipedia, it is our goal to work through the list over the next 12 months and add in new Cochrane content. We are recruiting editors for this new task through Cochrane's TaskExchange or visit the project page directly and start editing!
Cochrane Reviews are updated regularly based on need and updated reviews receive a new citation on MedLine. Once these updates are published, the next step is to update the citation within the Wikipedia article and make sure that the new conclusions are reflected on Wikipedia. Out of date Cochrane Reviews are flagged automatically in Wikipedia with the "Cochrane-Update-Bot", that is now run once a month. This volunteer task does not take a lot of time to perform, but the potential impact is very large. Between May 2017–October 2017, volunteers updated 340 Wikipedia articles and the articles have already received close to 32 million views. Please check our project updates page for articles newly eligible to update.
If you are interested in becoming involved or want more information, please visit the Cochrane-Wikipedia Initiative project page or contact User:JenOttawa.
Jennifer Dawson works with Cochrane’s Communications and External Affairs team as a Wikipedia Consultant. Her role includes maintaining and building further relations with Wikipedia, connecting new editors to the Wikipedia community, and supporting requests for engagement in Wikipedia work from the Cochrane community.
New requests since the last issue of The Signpost include:
The two requests mentioned above were accepted as cases Joefromrandb and others and Civility in infobox discussions
A bicyclist was hit. The driver fled the scene. Left in critical condition, a Reddit user by the name of YoungSalt desperately posted on several forums with a picture of the bumper. "Help identify this piece of a bumper from a hit and run with a cyclist now in critical condition." Using, among other sources, an image from Wikipedia (File:2009 Toyota Camry (ACV40R) Ateva sedan (2015-05-29) 01 (cropped).jpg) other users from Reddit were able to determine that the bumper fragment came from a 2009 Toyota Camry, and the previously unknown attacker was caught. Free culture is valuable for its own sake but even mundane pictures of cars can make a tangible difference in the world.
Ccable62, at a glance would appear to be a very obsessive fan of Tom Cable, removing allegations of violence against the football coach repeatedly. However, it turns out that, as The Wall Street Journal and the New York Post reported, Ccable62 is in fact Carol Cable, Tom's wife. Clearly, they felt that the allegations were unfounded, writing "ALL ACCUSATIONS AGAINST COACH CABLE WERE ORICRN VIA NFL. DA. AND POKICE TO BR ABSOLUTELY FALSE. THEY SHOULD NOT LIST LIES AND FALSR ACCUSATIONS IN THIS WIKIPEDIA AS IT IS SLANDER" in an edit summary. For now the allegations remain up, and Ccable62 has not edited since January 5.
When the University of Central Florida football team went undefeated for 13 games, everyone knew that controversy would ensue. As College football national championships in NCAA Division I FBS do not have a championship, there is no defined winner other than who has the best record. Many, however were and are of the opinion that Alabama truly won the division, and those people edited as such. Edit wars broke out across the spectrum, with an edit every 97 seconds on the 2017 UCF Knights football team page. Discussions broke out as to the color of the 2017 season at pages including coach Scott Frost, UCF Knights football, and the 2017 Alabama Crimson Tide football team (That page underwent 252 edits from mid-November to mid-January; of those, 124 came on January 8 and 9). (Originally reported in Sports Illustrated.)