Growth/Personalizovaný první den/Strukturované editace

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Growth

Nápověda: Použití nástrojů: (Panel Potřebuji pomoc , Aktivace Domovské stránky , Jak se stát mentorem nováčka? , Editační tipy )

Tato stránka popisuje práci týmu Growth na projektu strukturovaná editace. Tento projekt souvisí s dalšími projekty týmu Growth: Editačními tipy a Domovskou stránkou. Tato stránka obsahuje nejdůležitější informace, otevřené otázky a rozhodnutí. Více novinek týkající se práce týmu Growth najdete na všeobecné stránce s aktualizacemi. Závažné a větší aktuality budou pak vloženy i sem.

This page is about the general "structured task" concept, with some discussion of specific task types that we could build. Following this general discussion, the team began designing and engineering on those specific task types. Those task types have their own project pages, where most new information is being posted:

Současný stav

Shrnutí

Tým Growth nasadil Editační tipy v listopadu 2019, což nováčkům ukázalo články, které by mohli editovat, na jejich Domovské stránce. V dubnu 2020 byly tyto články generovány pouze na základě údržbových šablon vložených zkušenými editory, což nováčkům neumožňuje přesně určit, jaké sekce, slova či sekce potřebují jejich pozornost. I přes to ale nadšeně pozorujeme, že nováčci produktivně editují. As of April 2020, the suggested articles are sourced only from articles that have maintenance templates applied by experienced editors, which do not give newcomers particular direction on which sentences, words, or sections specifically need attention. Despite this lack of direction, we are happy to see that newcomers have been making productive suggested edits.

Ačkoliv údržbové šablony poskytují nováčkům velké množství různých tipů, kterým by se mohli věnovat, jsou velmi obsáhlé, aby s nimi nováčci snadno uspěli. Na mobilních zařízeních je navíc velmi těžké používat jakýkoli editor - ať už vizuální, nebo wikitextový.

Z tohoto důvodu jsme se rozhodli experimentovat s nápadem strukturované editace. To znamená, že rozebereme každý editory používaný postup na jednotlivé kroky, které jsou pro nováčky snadno uchopitelné. Podle výsledků jazykového týmu a týmu pro Androidovou aplikaci soudíme, že to pomůže nováčkům snadno udělat více editací, a to i na mobilu. Tato strukturovaná editace bude dostupná nováčkům jako součást editačních tipů. This is about breaking down editing workflows into a series of steps that newcomers can accomplish easily. Following the successful examples from Android and Language team work, we think these types of edits will be easier for newcomers to do and easier to do on mobile, helping more newcomers do more edits. These structured tasks would be accessible to newcomers as part of the newcomer tasks project.

Pozadí

Editování je komplikované

Podle naší předchozí práce soudíme, že první okamžiky nováčka rozhodují o tom, zda na projektu zůstane, či nikoliv. Věříme, že nováčci zůstávají, pokud dokážou rychle něco změnit, a mít tak pozitivní zážitek. Bohužel, editování Wikipedie – téměř jakýkoliv typ příspěvku – je obtížný, což znesnadňuje uspět. Například, pokud chcete přidat do článku jedinou větu, musíte provést zhruba tucet kroků. We believe that newcomers want to stay when they can quickly make an edit and have a positive experience. But contributing to Wikipedia -- almost any type of contribution -- is complicated, and this makes it hard for them to succeed quickly. For instance, there are about a dozen steps required in order to do something as simple as adding a single sentence to an article:

  1. Nalézt správný článek
  2. Zjistit, zda náhodou tato informace již v článku není
  3. Vybrat sekci, do které větu přidáte
  4. Kliknout na tlačítko Editovat
  5. Vložit větu na správné místo
  6. Klikněte na tlačítko Citace
  7. Vraťte se do zdroje informace, a zkopírujte si odkaz či získejte citační informace
  8. Vyplňte a uložte citační formulář
  9. Klikněte na tlačítko Zveřejnit změny
  10. Vyplnit shrnutí editace
  11. Zveřejnit

Nováčci, kteří vidí editor poprvé v životě, neví, jaké tyto kroky jsou, v jakém pořadí by je měli dělat, a jaké tlačítka mají přesně stisknout, aby se to stalo. Jinými slovy, jejich zážitek není strukturován. Nováček se může cítit přetížen, a odejít. Nebo může využít metody pokus-omyl, což často má za následek negativní zpětnou vazbu od dalších, zkušenějších, wikipedistů, což nováčka rovněž může odradit. To je to, o čem je tento projekt: "jak pomoci nováčkům dělat kroky ve správném pořadí?" In other words, their experience is not structured. They may just be overwhelmed and leave. Or they may use trial-and-error, make a mistake, and get negative feedback from experienced editors. That's what this project is about: how might we help newcomers step through these workflows in the right order?

Sekce níže se mohou během několika týdnů výrazně změnit, jsou příliš technické anebo nejsou relevantní pro porozumění tomuto projektu. Rozhodli jsme se proto je nepřeložit. Jejich překlad je dobrovolný

Založeno na znalosti dalších týmů

Hotcat strukturuje proces přidávání kategorií.

Přidávání struktury do editačních postupů je již dlouhou dobu tradiční součástí kultury Wikimedia. Některé příklady:

  • HotCat: umožňuje uživatelům vybrat, které kategorie přidat na pár kliknutí, namísto manuální editace wikitextu.
  • Commons Upload Wizard: breaks the process of uploading media to Commons into a series of a simple steps.
  • Citoid: available in the Visual Editor, this breaks down the process of adding a citation into steps that include algorithms to automatically produce the citation text and template.

Most recently, the idea of "structured tasks" has been working well on the Wikipedia Android app and in the Content Translation tool. We're inspired by their work.

With their "suggested edits" project, the Android team broke down the process of adding a title description to a Wikipedia article into one easy step of typing into a text box. They have since done the same with translating title descriptions across languages. In order to do the same tasks without a structured workflow, users would have to go to Wikidata and go through several steps to make those same edits. The team learned that this method works: many Android users make hundreds of these small contributions.

The Language team built the Content Translation tool, which does several things to structure the process of translating an article. It offers a side-by-side interface built for translations, it breaks the translation down into sections, and it automatically applies machine translation algorithms. Though Wikipedians could translate articles before the existence of the tool, the number of manual steps required made it very difficult. This tool is successful, with hundreds of thousands of translations completed.

We learned that when translating an article is broken down into steps, with rote parts (e.g. running machine translation) taken care of automatically, more articles get translated.

The Growth team is thinking about applying these same principles to content edits in articles, like adding links, adding images, adding references, and adding sentences.

Návrh, jak by strukturované editace mohly vypadat

Nejlepším způsobem, jak ukázat, co tímto projektem máme na mysli, je ukázáním rychlého grafického návrhu. První ze strukturovaných editací, o které jsme přemýšleli. Tatáž myšlenka se ale dá aplikovat i na "přidání obrázku", "přidání reference" nebo dokonce i "přidání informace".

V editačních tipech je k dispozici úkol "přidání odkazu" – v rámci něj mají do článku přidat modrý vnitřní odkaz. To by mělo být jednoduché. Myslíme si, že nováčci nerozumí tomu, v jakém pořadí mají provést jednotlivé kroky vedoucí k přidání odkazu, nebo nemusí vědět, jaké slovy by měly být odkazem. Představujeme si rozhraní, které nováčky krok za krokem provede přidáním odkazu, za pomoc algoritmu, který doporučí slova či fráze, které by měly být odkazem. This seems like a simple editing task to get started. But we think that many newcomers may not understand how to go through the steps of adding a link and may not know which words to make into links. We're imagining a workflow that walks them through it, step-by-step, with the assistance of an algorithm that can guess which words or phrases might make the best links.

Ve návrhu níže uvidíte nováčka, který si otevře článek k editaci, a systém mu nabídne slovo, které by mohlo být dobrým odkazem. Pokud si myslí, že by slovo odkazem být mělo, systém nováčka provede přidáváním odkazů – a možná v této aktivitě budou pokračovat. Na algoritmu momentálně pracuje výzkumný tým nadace Wikimedia, jehož předběžné výsledky nám ukazují, že by vybudování takového algoritmu mělo být možné. If they agree that it should be made a link, they are walked through the steps of making the link. This will hopefully teach them to add links on their own in the future -- and perhaps they'll enjoy continuing to receive these algorithmic link suggestions. Regarding the algorithm, the WMF Research team has done some preliminary work that makes us confident that such an algorithm is possible.

Sketch of an idea for a structured workflow for adding links to an article, aimed toward teaching newcomers how to add links on their own.

Jak jsme o tomto nápadu dále přemýšleli, napadlo nás to vzít za jiný konec. Namísto toho nováčky naučit, jak se ve vizuálním editoru přidávají odkazy, můžeme nováčkům předložit snadný nástroj, kterým pouze potvrdí či zamítnoudoporučení algoritmu, a systém uloží editaci za ně. Ačkoliv toto nováčky nikdy nenaučí, jak editovat po vlastní ose, může to pomoci nováčkům, kteří pouze chtějí rychle pomoci. Může to také být dobré pro uživatele, kteří chtějí udělat pouze pár rychlých editací, podobně, jako má Androidová aplikace velké množství uživatelů, kteří chtějí pouze opravovat popisky článků. Instead of being aimed toward teaching the newcomer to add links using the visual editor, this next workflow lets the user quickly confirm or reject recommendations from the algorithm, directly editing the article. While it does not teach them how to add links via the editor, it might help a newcomer edit at high volume, and might be a better fit for a user who is trying to be productive with simple tasks while they are on the go. Or perhaps might be a good fit for users who only are interested in very simple edits, similarly to how the Android app has many editors who only want to write title descriptions.

Sketch of an idea for a structured workflow for adding links to an article, aimed toward helping newcomers edit at high volume.

Jak jsme o strukturovaných editacích dále přemýšleli, uvědomili jsme si, že stojíme před velkou otázkou: Měl by se náš produkt zaměřit na použití tradičních nástrojů, nebo by měl umožnit nováčkům rychle uložit větší množství editací?

Why this idea is prioritized

Myslíme si, že možnost rychle uložit produktivní editaci pomáhá nováčkům uspět. Jakmile mají za sebou pár editací, zbytek z wiki-dovedností přichází snáz. Nováčci mohou snadno vidět dopad jejich editací, dostat poděkování, zeptat se informovaně na otázky, vytvořit si uživatelskou stránku apod. Proto chceme, aby většina nováčků rychle uložila nějakou editaci. Z projektu Editačních tipů je zřejmé, že nováčci hledají jednoduché úkoly, na kterých by mohli pracovat. Zároveň jsme ale pozorovali následující: Once they've done some edits, the rest of the wiki experience quickly becomes richer. Newcomers can then see their impact, get thanked, ask informed questions to their mentors, create their userpage, etc. Therefore, we want lots of newcomers to make their first edits as soon as possible. We have already seen from the newcomer tasks project that many newcomers are looking for easy tasks to do. But we also have observed these things:

  • Pouze 25 % nováčků skutečně edituje článek, co si vybrali
  • Pouze 25 % z těch, kdo editují, jdou i na další článek
  • Je zde i pár nováčků, kteří jsou pro Editační tipy nadšeny - a každý den splní několik z nich. To umožňuje nováčkům udělat hodně wiki-práce.
  • Během testování s uživateli jsme si všimli, že nováčky často zajímá, co konkrétně by měli v článku změnit. Jinými slovy, editování celého článku je příliš otevřeným úkolem.

Taking these points along with the experiences described above of the Android and Content Translation teams, we think we could increase the number of newcomers editing and continuing to edit by structuring some of the content editing workflows in Wikipedia.

Příležitosti pro strukturované editace

When we break down editing workflows into steps, we call them "structured tasks". Here are some of the possible benefits we think could come from structured tasks:

  • Make it easy for newcomers to make meaningful contributions.
  • Develop editing workflows that make sense for mobile. Mobile design principles tell us that users should see one step at a time, not a complicated workspace.
  • Let newcomers increase their skills incrementally. They could take on successfully more challenging types of tasks.
  • Let people find an editing experience that fits them. By giving newcomers a feed of structured tasks, they could find the type of tasks that they prefer.
  • Perhaps similar workflows could be opened to experienced editors in the future.

Concerns and downsides to structured tasks

Whenever we add new ways for people to edit Wikipedia, there are many things that can go wrong:

  • By making editing too quick and easy, we may attract vandals, or users who don't apply enough care when editing.
  • Giving newcomers simple workflows may keep them from learning the traditional editing tools, which are essential for doing the most impactful wiki work.
  • Structured tasks may not be good at accounting for differences across languages, idiosyncrasies with wikitext, and could cause other kinds of bugs.
  • Algorithms that surface structured tasks may not be accurate enough, and falsely encourage newcomers to complete edits they shouldn't.

Community discussion

In May 2020, we conducted discussions with community members in six languages (English, French, Korean, Arabic, Vietnamese, Czech) about the above ideas for structured tasks. The English discussion mostly took place on the discussion page here, with other conversations on English Wikipedia, and local language conversations on the other five Wikipedias. We heard from 35 community members, and this section summarizes some of the most popular and interesting thoughts. These discussions heavily influenced our next set of designs.

  • Community members were generally positive about the potential for structured tasks to help newcomers start editing. But it was also a widely expressed view that it's important for newcomers to be introduced to the conventional source and visual editors during the process. Community members want to make sure that newcomers are not siloed in a separate editing experience, and that they can find their way to more valuable edits.
  • The Czech community talked about ideas for how the structured tasks can place inside the visual editor, so that newcomers can start getting used to being in the editor. Perhaps the editing tools that are not needed for the structured task can be grayed-out.
  • Community members asked why we are choosing "add a link" as our first structured task, as opposed to higher-value types of edits. We talked about how this task is one of the easiest for us to build, which will help us prototype and learn from structured tasks sooner, and how it is a comparatively low-risk task, with fewer opportunities for newcomers to damage articles.
  • Several communities mentioned that spelling corrections would be a particularly valuable task, and we talked about technical options for how to generate lists of potential spelling mistakes. See these notes for more details.
  • We also talked about whether reverting vandalism is a good fit for newcomers. It doesn't seem like the answer is clear, and this will have to be discussed more in the future.
  • An idea that was mentioned multiple times is how to "step newcomers up" to progressively more challenging tasks, perhaps while giving them rewards for successfully completing easier ones.

Types of tasks

There are many different editing workflows that have the potential to become structured. We began to list workflows when we first designed the newcomer tasks workflow here, and we have since narrowed down to a shorter list of task types that seem best suited to being structured. The table below contains that short list, ranked in a potential priority order.

Potential priority Task type How it might work Advantages Concerns
1 Add a link For articles without enough wikilinks, an algorithm (existing) suggests words or phrases that should become wikilinks, and the newcomer accepts or rejects the suggestions. Linking is a quick and easy way to edit, and has low potential to damage articles. Understanding when to add a link takes judgment, and we don't want articles to be overlinked. It is also not the most valuable type of edit.
2 Add an image For articles without an illustration, an algorithm (potential) suggests an image from Commons. This might be a simple algorithm that just looks at what images are used on that article in other languages. The newcomer decides if the image belongs, and where in the article to add it. Good images make a big difference in an article, and newcomers are interested in adding images. Adding the wrong image to an article could damage the article in a very visible way.
3 Add a reference Some sentences or paragraphs clearly need citations. An algorithm (in development) would point out which sentences likely need suggestions, and the newcomer would seek sources to add as citations in a step-by-step workflow. References are of clear importance to the core of the encyclopedia. This task may not be exciting to newcomers. They may also struggle to find and use sources without guidance.
4 Copyedit Using open-source spellcheck dictionaries and code, or using Wiktionary, identify likely misspelled words, and point them out to newcomers, who can use the visual editor or wikitext editor to fix them one at a time. Clearly valuable and needed in any wiki, satisfying to newcomers. Helps them start editing the main text of articles, as opposed to peripherals parts of the article. Scaling to any language may be difficult, depending on the availability of good spellchecking algorithms.
5 Add a section An algorithm detects when an article could use additional sections, based on the kinds of section headers that similar articles have (e.g. all biographies of scientists tend to have "Publications" sections). The newcomer is walked through producing a well-referenced paragraph. Real content additions that could help close knowledge gaps. A much more challenging task than the others, requiring many wiki skills to be used together. May produce low-quality content.

Prioritizing "add a link"

The Growth team currently (May 2020) wants to prioritize the "add a link" workflow over the other ones listed in the table above. Although other workflows, such as "copyedit", seem to be more valuable, there are a set of reasons we would want to start first with "add a link":

  • In the near term, the most important thing we would want to do first is to prove the concept that "structured tasks" can work. Therefore, we would want to build the simplest one, so that we can deploy to users and gain learnings, without having to invest too much in the first version. If the first version goes well, then we would have the confidence to invest in types of tasks that are more difficult to build.
  • "Add a link" seems to be the simplest for us to build because there already exists an algorithm built by the WMF Research team that seems to do a good job of suggesting wikilinks (see the Algorithm section).
  • Adding a wikilink doesn't usually require the newcomer to type anything of their own, which we think will make it particularly simple for us to design and build -- and for the newcomer to accomplish.
  • Adding a wikilink seems to be a low-risk edit. In other words, the content of an article can't be as compromised through adding links incorrectly as it could through adding references or images incorrectly.

Notes on "copyedit"

In conversations with community members on this project's discussion page, many people brought up the question of how to make a structured task around copyediting. Correcting spelling, grammar, punctuation, and tone seemed to everyone to be a clearly useful task that should be prioritized. The Growth team initially shied away from this workflow because of scaling concerns: even if we were able to find or develop an algorithm that could reliably find copyedits in one language, would we be able to do that in dozens of other languages?

We began to learn more about this by talking with User:Beland, who developed the "moss" script for English Wikipedia's Typo Team. We wanted to understand how the process works, and what it might look like to do something similar in other languages. In short, it sounds like the most promising avenue is through existing open-source spellcheckers and dictionaries. Two examples are the aspell and hunspell libraries. Below are our notes from learning about "moss" with User:Beland.

  • Prospects for doing something similar in other languages
    • A process like this should theoretically work in other languages, given that other languages also have Wiktionaries and open-source spellcheckers.
    • But it would not be possible to deploy in a new language without native speakers validating it. There would likely need to be customization for many languages.
    • Likely more challenges for languages without word segmentation (e.g. Japanese).
    • Likely more challenges for agglutinative languages.
    • Different projects have differing manuals of style, which may cause issues.
    • If an algorithm is performing poorly, it should always be possible to change its thresholds so that it identifies fewer potential errors, but with higher confidence.
  • How does moss work?
    • Download the dump files of all of English Wikipedia every two weeks.
    • In order to cut down on false positives, remove templates and everything inside quotation marks, etc.  Only want to work on the main text in the article: the things written “in Wikipedia’s voice”.
    • Check that every word is in English Wiktionary.
    • Uses Python NLTK (natural language toolkit) for word segmentation.
    • Looks at edit distance to classify misspellings.  e.g. “T1” is one edit distance (95% precision).  Also classifies “TS” whitespace errors.
    • Also includes an English open-source spellchecker to narrow the search space so that the algorithm can run faster.
    • He has also started trying to add grammar rules (e.g. identifying passive voice), but that’s more experimental, and much more difficult than spelling.
    • At the end of the process, it produces a list of articles and likely typos.  The user opens the article and searches for the likely typo.

Many copyedit requests are also editors whose native language is not English, asking for English polishing. See WikiProject Guild of Copy Editors.