Wikipedia:Simple talk

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Wikidata: Access to data from arbitrary items is here[change]

VisualEditor News #4—2015[change]

Elitre (WMF), 22:28, 14 August 2015 (UTC)

Wikidata[change]

If you're not already familiar with how to use Wikidata, I'd like to suggest that you look into learning about it. Here is some of what it can do for us:

  • Interwiki language links: Any time you create an article, category or template that also exists on another Wikipedia, you can (and probably should) create an interwiki language link for it in Wikidata (but only if it's an exact match). These links used to be stored in individual pages on each Wikipedia, but now they need to be in Wikidata. If you see any of these links in articles, categories, or templates, it's a good idea to migrate them to Wikidata. Feel free to ask for help with that if you need it.
  • Retrieving basic data: Wikidata stores basic information about many different kinds of things. The information for most fields in infoboxes can be stored in Wikidata and retrieved from there. For a person, the information can include birthdate, awards the person has received, their spouse and children, schools they attended, and lots more. For each different kind of thing (person, city, company, etc.), there are different kinds of information that Wikidata can store. References for each item can also be stored.
    Getting information from Wikidata (instead of hardcoding it here) can help us keep our articles updated when it comes to information that changes over time. You can see an example of retrieving information from Wikidata in two templates that are used by our article Ramelteon. Template:Wikidata chemical formula retrieves the chemical formula from the Wikidata entry for Ramelteon. Template:Significant drug interaction retrieves information about drug interactions. If new drug interactions are discovered and entered in Wikidata, the new information will appear here without anyone having to change the article. Cool, huh? You can look at the Wikidata item for Ramelteon to see how that information is stored.

I hope we will use the information in Wikidata more and more.

There's a newsletter that gives information about Wikidata news. If you'd like to subscribe to it, go to m:Global message delivery/Targets/Wikidata (that's on Meta-Wiki) and add yourself to the list. The newsletter will be added to your talk page (or other page you specify) each time it comes out.

I now return you to your previously scheduled editing. Let me know if you have any questions. --Auntof6 (talk) 07:18, 16 August 2015 (UTC)

Wiki labels & Revision Scoring as a Service for Simple English Wikipedia[change]

Hello Simple English Wikipedia,

I apologize for my complete lack of Simple English skills. I would most welcome if my post is translated to Simple English.

So computers are very good at crunching numbers. Your average calculator can out smart you in arithmetic. However computers are terrible at pretty much in everything else. Programming computers to under take any task no matter how simple beyond computing tends to be very difficult. This is where Artificial Intelligence comes in. With Artificial Intelligence we teach computers how to solve problems without explicit programming for the solution. This is what we are doing.

We are working on a project called m:Research:Revision scoring as a service which aims to provide quality control Artificial Intelligence infrastructure for Mediawiki and Wikimedia projects. We already have our system implemented and running on Azerbaijani, English, French, Simple English, Persian, Portuguese, Spanish, Turkish and Vietnamese editions on Wikipedia. We are hoping to adapt our tool to serve Simple English language as well as a number of other languages.

We are currently mainly focusing on vandalism detection where we provide an API (m:ORES) that provides scores. We have made an effort to keep our system robust.

The examples I'll provide are based on a machine learning algorithm that was trained to use 20,000 reverted edits. This is kind of modelling is problematic for two reasons. First is, there are non-vandalism related reasons for edits to be reverted such as mistakes from new users, this would develop such an unproductive bias. Second problem would be it lacks the ability to distinguish good faith users from malicious ones. To demonstrate our system I will give three examples from English wikipedia. I have picked these three semi-random.

  • Score of 90% diff en:Moncef Mezghanni
    • As visible in the diff, it is clearly something that shouldn't be welcome on English wikipedia. Algorithms confidence also matches my human assessment.
  • Score of 75% diff en:Monin
    • When I look at the diff it isn't immediately clear to me if this should be reverted. Detailed look reveals that prior version had more neutral information, but new version at a glance isn't exactly clear cut vandalism, albeit spammy. Algorithms confidence drops just as my human assessment.
  • Score of 19% diff en:Curiosity killed the cat, but satisfaction brought it back
    • As visible in the diff this edit clearly improves the article. The algorithms confidence plummets as well. Algorithm is more confident that this edit should NOT be reveted.

We are also working towards a system for article quality where we use existing assessment by en:Wikipedia:Version 1.0 Editorial Teamto train our system. We only have this system on English wikipedia at the moment but we would be more than happy to expand to other language editions. I am uncertain if Simple English Wikipedia has a similar quality assessment scale. I have picked 5 random articles to demonstrate this.

Typical problem is that humans typically do not re-asses articles over time or articles are never assessed in the first place. Our system circumvents this problem by automating this.

We have already gathered some language features such as bad words and informal words.

We need a localization of en:Wikipedia:Labels serving as our local landing page. After this is done, we would like to start an edit quality campaign where we request the local community to hand code/label ~2000 revisions labeling them productive/damaging and good faith/bad faith. This would be similar to the campaign on English Wikipedia en:Wikipedia:Labels/Edit quality.

After this we will be able to generate scores for revisions that is usable by gadgets such as ScoredRevisions as well as (potentially) tools like huggle. If community desires it, it can even be used to create a local vandalism reversion bot.

So in a nutshell our algorithm relies on community input to support the community. Feel free to ask any questions. Either here, on meta or on IRC on the freenode server and #wikimedia-ai channel where we hang out. You can also reach us at https://github.com/wiki-ai

-- とある白い猫 chi? 11:46, 17 August 2015 (UTC)

Dealing with vandalism[change]

There is an editor who keeps vandalising Triangular number. What can be done about it?Kdammers (talk) 13:15, 18 August 2015 (UTC)

How can we improve Wikimedia grants to support you better?[change]

My apologies for posting this message in English. Please help translate it if you can.

Hello,

The Wikimedia Foundation would like your feedback about how we can reimagine Wikimedia Foundation grants, to better support people and ideas in your Wikimedia project. Ways to participate:

Feedback is welcome in any language.

With thanks,

I JethroBT (WMF), Community Resources, Wikimedia Foundation.

(Opt-out Instructions) This message was sent by I JethroBT (WMF) through MediaWiki message delivery. 23:08, 18 August 2015 (UTC)

Patrol backlog[change]

Calling all patrollers: we have a backlog in the article and template areas. Help would be appreciated. Please remember that before marking something as patrolled, it should be checked to be sure it's in decent shape: written in simple language, has appropriate references, is properly categorized, isn't a copyvio, etc. Whatever you do, please don't mark a page patrolled just to get it done: if you don't want to do the checking, that's OK, just leave it for someone else. Thanks! --Auntof6 (talk) 06:26, 25 August 2015 (UTC)