Thanks for the thoughtful comments, Kerry! There were many great points in your email, I'd like to focus on some of them.
Your likening of viewership to readers and inlinks to writers echoes how we think about this as well. I agree that these two groups differ on many characteristics, something both the contributor surveys you mention shows, as well as research. For example West et al's 2012 paper (see citation below) looks at how the browsing history shows differing interests between readers and contributors, and the "WP:Clubhouse" paper (Lam et al, 2011) starts getting at how the gender proportions differ (there are of course other papers as well, these were the first that came to mind). By combining both, we get more signal.
This also touches on the discussion of how popularity is related to importance, and whether importance changes over time. The article about Drottninggatan in Stockholm is but one example of an article that becomes the center of attention due to a breaking news event. We did an analysis of a dataset of very popular articles in our 2015 ICWSM paper, finding that about half of them show this kind of transient behaviour. In that paper we argue that the more popular articles are more important and should have higher quality, which means that it's partly chasing a moving target and partly a focused effort on the long-term important content (of which pasteurization is probably one example). For some topics it is easier to predict their shifts in importance because they are seasonal, e.g. christmas, easter, or sporting events like world championships. When it comes to others it might be harder, e.g. Trump, or Google Flu Trends, which I recently came across. How important is the latter article now that the website is no longer available?
When it comes to links, you point out that they are not all equal. This is something we're incorporating in our work. Currently we have a model for WikiProject Medicine, and it accounts for both inlinks from all across English Wikipedia, as well as to what extent they come from other articles tagged by the project. We also use the clickstream dataset to add information about whether an article's traffic comes from other Wikipedia articles, meaning it is useful as supporting information for those, or whether it comes from elsewhere. Lastly, we use the clickstream dataset to get an idea about how many inlinks to an article are actually used. As you write, the links in the lede are more important, something at least one research paper points to (Dimitrov et al, 2016), and something the clickstream dataset allows us to estimate. I think it's great to see these ideas pop up in the discussion and be able to show how we're incorporating these into what we're doing and that they affect our results.
As I wrap up, I would like to challenge the assertion that initial importance ratings are "pretty accurate". I'm not sure we really know that. They might be, but it might be because the vast majority of them are newly created stubs that get rated "low importance". More interesting are perhaps other types of articles, where I suspect that importance ratings are copied from one WikiProject template to another, and one could argue that they need updating. Our collaboration with WikiProject Medicine has resulted in updated ratings of a couple of hundred or so articles so far, although most of them were corrections that increase consistency in the ratings. As I continue working on this project I hope to expand our collaborations to other WikiProjects, and I'm looking forward to seeing how well we fare with those!
Citations: West, R.; Weber, I.; and Castillo, C. 2012. Drawing a Data-driven Portrait of Wikipedia Editors. In Proc. of OpenSym/WikiSym, 3:1–3:10.
Lam, S. T. K.; Uduwage, A.; Dong, Z.; Sen, S.; Musicant, D. R.; Terveen, L.; and Riedl, J. 2011. WP:Clubhouse?: An Exploration of Wikipedia's Gender Imbalance. In Proc. of WikiSym, 1–10.
Warncke-Wang, M., Ranjan, V., Terveen, L., and Hecht, B. "Misalignment Between Supply and Demand of Quality Content in Peer Production Communities" in the proceedings of ICWSM 2015.
Dimitrov, D., Singer, P., Lemmerich, F., & Strohmaier, M. (2016, April). Visual positions of links and clicks on wikipedia. In Proceedings of the 25th International Conference Companion on WWW (pp. 27-28).
Cheers, Morten
On 25 April 2017 at 20:39, Kerry Raymond kerry.raymond@gmail.com wrote:
Just a few musings on the issue of Importance and how to research it ...
I agree it is intuitive that importance is likely to be linked to pageviews and inbound links but, as the preliminary experiment showed, it's probably not that simple.
Pageviews tells us something about importance to readers of Wikipedia, while inbound links tells us something about importance to writers of Wikipedia, and I suspect that writers are not a proxy for readers as the editor surveys suggest that Wikipedia writers are not typical of broader society on at least two variables: gender and level of education (might be others, I can't remember).
But I think importance is a relative metric rather than absolute. I think by taking the mean value of importance across a number of WikiProjects in the preliminary experiment may have lost something because it tried (through averaging) to look at importance "generally". I would suspect conducting an experiment considering only the importance ratings wrt to a single WikiProject would be more likely to show correlation with pageviews (wrt to other articles in that same WikiProject) and inbound links. And I think there are two kinds of inbound links to be considered, those coming from other articles within the same WikiProject and those coming from outside that Wikiproject. I suspect different insights will be obtained by looking at both types of inbound links separately rather than treating them as an aggregate. I note also that WikiProjects are not entirely independent of one another but have relationships between them. For example, The WikiProject Australian Roads describes itself as an "intersection" (ha ha!) of WikiProject Highways and WikiProject Australia, so I expect that we would find greater correlation in importance between related WikiProjects than between unrelated WikiProjects.
When thinking about readers and pageviews, I think we have to ask ourselves is there a difference between popularity and importance. Or whether popularity *is* importance. I sense that, as a group of educated people, those of us reading this research mailing list probably do think there is a difference. Certainly if there is no difference, then this research can stop now -- just judge importance by pageviews. Let's assume a difference then. When looking at pageviews of an article, they are not always consistent over time. Here are the pageviews for Drottninggatan
https://tools.wmflabs.org/pageviews/?project=en.wikipedia. org&platform=all-access&agent=user&range=latest-90&pages=Drottninggatan
Why so interesting on 8 April? A terrorist attack occurred there. This spike in pageviews occurs all the time when some topic is in the news (even peripherally as in this case where it is not the article about the terrorist attack but about the street in which it occurred). Did the street become more "important"? I think it became more interesting but not more important. So I think we do have to be careful to understand that pageviews probably reflect interest rather than importance. I note that The Chainsmokers (a music group with a number of songs in the current USA music charts) gets many more Wikipedia article pageviews than the Wikipedia article on Pasteurization but The Chainsmokers are not rated as being of high importance by the relevant WikiProjects while Pasteurization is very important in WikiProject Food and Drink. Since pasteurisation prevents a lot of deaths, I think we might agree that in the real world pasteurisation is more important than a music group regardless of what pageviews tell us.
https://tools.wmflabs.org/pageviews/?project=en.wikipedia. org&platform=all-access&agent=user&range=latest-90&pages=The_Chainsmokers| Pasteurization
Of course it is matters for Wikipedia's success that our *popular* articles are of high quality, but I think we have be cautious about pageviews being a proxy for importance.
When we look at Wikipedia writers' decisions in tagging the importance of articles to WikiProjects, what do we find? As we know, project tags are often placed on new articles (and often not subsequently reviewed). So while I find that quality tags are often out-of-date, the importance seems to be pretty accurate even on a new stub articles. This is because it is the importance of the *topic* that is being assessed which is independent of the Wikipedia article itself. Provided the article is clear enough about what it is about and why it matters (which is the traditional content of that first paragraph or two and failing to provide it will likely result in speedy deletion of the new article), assessment of the topic's importance can be made even at new stub level. This tells us that importance for Wikipedia writers is determined by something outside of Wikipedia (probably their real-world knowledge of that topic space -- one assumes that project taggers are quite interested in the topic space of that project). While article quality hopefully improves over time, I would be surprised if article importance greatly changed over time. Obviously there are counter-examples. I am guessing Donald Trump's article may have grown in importance over time but that's probably because his lede para changed. Adding President of the USA into the lede paragraph makes him much more important than he was before in the real world and internal to Wikipedia he has acquired an inbound link from the presumably high-importance President of the USA article. So I think it might be interesting to study those articles whose importance does change over time to see if there are any strong correlations with what is happening to the article inside Wikipedia. I think it is this set of importance-changing articles may be where we really learn what Wikipedia article characteristics are strongly correlated to "importance" given that importance itself appears to be pretty stable for most articles.
Although not stated explicitly, I imagine we believe that generally less important articles tend to link to more important articles but more important articles don't link to less important articles. And hence in-bound links are likely to matter in assessing importance and that in-bound links from "important" articles are more valuable than in-bound links from less important articles (which creates something of a bootstrapping problem) similar to the issue to Google's PageRank algorithms. But I think we do have some information that Google doesn't have. The average webpage does not have a lede paragraph that situates the topic relative to other topics; a Wikipedia article does. If I have to choose to define Thing X in terms of Thing Y, it tends to suggest that Y is more important than X. If Y also defines itself in terms of X, then it tends to suggest they are equivalent in importance at some way. Indeed I suspect when we get to the VERY IMPORTANT topics we will see this kind of circular definition (e.g. you see circular definitions in Wikipedia around Philosophy and Knowledge). Aside, if you have never done this before, try this experiment. Choose a random article (left hand tool bar in Desktop Wikipedia), then click the first link in the article that matters (i.e. ignore links hatnotes or links inside parentheses). Repeat this first link clicking and sooner or later you will reach articles like Knowledge and Philosophy, which all sit inside circular definition groups.
If we look at the Donald Trump article, his first sentence contains only two links, one to List of Presidents of the USA and the other to President of the USA. If we look at the those two articles, we find that both of them mention Donald Trump in their lede paras (although not as early as the first sentence) and before mentions of any other US President elsewhere in the article. Which is consistent with what we know about the real world, the role of the President is more important than its officeholders and that the current officeholder has more importance than a past officeholder. So topic importance does seems to be skewed towards the "present day".
So I suspect the links in the lede paras are of greater relevance to the assessment of importance than links further down in the article which will be more likely relate to details of a topic and may include examples and counter-examples (this is a way in which high importance article may mention much lower importance articles). However, we do have to be a little bit careful here because of the MoS practice of not linking very common terms. For example, an Australian article will often refer to Australia in the lede para but it will almost certainly not be linked to the Australia article (and any attempt to add such a link will likely see it removed with an edit summary that mentions [[WP:Overlinking]]) whereas there is no problem if you link to an Australian state article, e.g. New South Wales. So we might find that some very important topics that often appear in ledes might get fewer links that you might expect because of the MoS policies on overlinking, which may be problem when working with inbound links. It may be that for "very common topics" the presence of the article title (or its synonyms) in the lede may have to be considered as if it were an in-bound link for statistical research purposes.
Given all of the above, perhaps the most interesting group of articles to study in Wikipedia are those articles whose manually-assessed importance has changed over the life of the article AND which were NOT current topics in the lifetime of Wikipedia (given the influence of "current" on importance). But having said that, I wonder if that group of articles actually exists. Recently a newish Australian contributor expressed disappointment that all the new articles they had created were tagged (by others) as of Low Importance. My instinctive reply was "that's normal, I think of the thousands of articles I have started only a couple even rated as Mid importance, this is because the really important articles were all started long ago precisely because they were important". I suspect topics that are very important (for reasons other than being short-lived importance due in being "current" in the lifetime of Wikipedia) will generally show up as having started early in Wikipedia's life and that those that become more/less important over time will be largely linked to becoming or ceasing to be "current" topics). E.g. article Pasteurization started in May 2001 saying nothing more than " Pasteurization is the process of killing off bacteria in milk by quickly heating it to a near boiling temperature, then quickly cooling it again before the taste and other desirable properties are affected. The process was named after its inventor, French scientist Louis Pasteur. See also dairy products." The links in this very first version are still present in its lede paragraph today, suggesting our understanding of "non-current" topics is stable and hence initial importance determinations can probably be accurately made. For Pasteurization the Talk page shows it was not project-tagged until 2007 when it was assigned High Importance as its first assessment.
I suspect we will find that initial manual assessment of article importance will be pretty accurate for most articles. And I suspect if we plot initial importance assessments against time of assessment, we will find the higher importance articles commenced life on Wikipedia earlier than the lower importance articles. If I am correct, then there isn't a lot of value in machine-assessment of importance of topics because it relates to factors external to Wikipedia and often does not change over time and therefore can often be correctly assessed manually even on new stub articles (and any unassessed articles can probably be rated as Low Importance as statistically that's almost certainly going to be correct). If a topic becomes more important due to "current" events, then invariably that article will be updated by many people and one of them will sooner or later manually adjust its importance. What is less likely to happen is re-assessing downwards of Importance when an important "current" topic loses its importance when it is no longer current, e.g. are former American presidents like Barack Obama or George W Bush or further back less important now? These articles will not be updated frequently once the topic is no longer in the news and therefore it is less likely an editor will notice and manually downgrade the importance, so there may be a greater role for machine-assessment in downgrading importance rather than upgrading importance.
Another area where there might be a role for machine-assessed importance in regards to POV-pushing where an POV-motivated editor might change the manual-assessment importance of articles to be higher or lower based on their POV (e.g. my political party is Top Importance, other parties are of Low Importance). I suspect that often a page watcher would correct or at least question that kind of re-assessment. However, articles with few active pagewatchers you might get away with POV-pushing the article's importance tag because nobody noticed. In this situation, a machine assessment could be useful in spotting this kind of thing.
This suggests that another metric of interest to importance might be number of pagewatchers, although I suspect that pagewatching may relate more to caring about the article than to caring about the topic. And one has to be careful to distinguish active pagewatchers (those who actually do review changes on their watchlists) from those who don't, as that may make a difference (although I am not sure we can really tell which pagewatchers are truly actively reviewing as a "satisfactory review" doesn't leave a trace whereas an "unsatisfactory" review is likely to lead to a relatively soon revert or some other change to the article, the article Talk or the User Talk of reviewed contributor which may be detectable).
The other aspect of articles that occurs to me as being possibly linked to importance of the topic would be use of the article as the "main" article for a category or as the title of a navbox (as it suggests that the articles in the category or navbox are in some way subordinate to the main/title article). Similarly for list articles, the "type" of the list is often more important than its instances).
Kerry
-----Original Message----- From: Wiki-research-l [mailto:wiki-research-l-bounces@lists.wikimedia.org] On Behalf Of Morten Wang Sent: Friday, 21 April 2017 6:04 AM To: Research into Wikimedia content and communities < wiki-research-l@lists.wikimedia.org> Subject: Re: [Wiki-research-l] Project exploring automated classification of article importance
Hi Pine,
These are great pointers to existing practices on enwiki, some of which I've been looking for and/or missed, thanks!
Cheers, Morten
On 19 April 2017 at 22:35, Pine W wiki.pine@gmail.com wrote:
Hi Nettrom,
A few resources from English Wikipedia regarding article importance as ranked by humans:
https://en.wikipedia.org/wiki/Wikipedia:Vital_articles
https://en.wikipedia.org/wiki/Wikipedia:Version_1.0_ Editorial_Team/Release_Version_Criteria#Priority_of_topic
https://en.wikipedia.org/wiki/Wikipedia:WikiProject_assessment#Statist ics
I infer from the ENWP Wikicup's scoring protocol that for purposes of the competition, an article's "importance" is loosely inferred from the number of language editions of Wikipedia in which the article
appears:
https://en.wikipedia.org/wiki/Wikipedia:WikiCup/Scoring#Bonus_points.
HTH,
Pine
On Tue, Apr 18, 2017 at 4:17 PM, Morten Wang nettrom@gmail.com wrote:
Hello everyone,
I am currently working with Aaron Halfaker and Dario Taraborelli at the Wikimedia Foundation on a project exploring automated classification of article importance. Our goal is to characterize the importance of an article within a given context and design a system to predict a relative importance rank. We have a project page on meta[1] and welcome comments
or
thoughts on our talk page. You can of course also respond here on wiki-research-l, or send me an email.
Before moving on to model-building I did a fairly thorough literature review, finding a myriad of papers spanning several disciplines. We have
a
draft literature review also up on meta[2], which should give you a reasonable introduction to the topic. Again, comments or thoughts (e.g. papers we’ve missed) on the talk page, mailing list, or through email are welcome.
Links:
classification_of_article_importance https://meta.wikimedia.org/wiki/Research:Automated_ classification_of_article_importance 2. https://meta.wikimedia.org/wiki/Research:Studies_of_Importance
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