Wikipedia:Wiki Ed/Wellesley College/Data and Text Mining for the Web (Spring 2017)

In the past decade, we have experienced the rise of socio-technological systems used by millions of people: Google, Facebook, Twitter, Wikipedia, etc. Such systems are on the one hand computational systems, using sophisticated infrastructure and algorithms to organize huge amount of data and text, but on the other hand social systems, because they cannot succeed without human participation. How are such systems built? What algorithms underlie their foundations? How does human behavior influence their operation and vice-versa? In this class, we will delve into answering these questions by means of: a) reading current research papers on the inner-workings of such systems; b) implementing algorithms that accomplish tasks such as web crawling, web search, random walks, learning to rank, text classification, topic modeling; and c) critically thinking about the unexamined embrace of techno-solutionism using a humanistic lens.

Week 1
Welcome to our Wikipedia project page. This page will guide you through the Wikipedia project for our course this week (and if chosen, through the rest of the semester).

Our project has been assigned a Wikipedia Content Expert. If you want to take this project a little further than just our work on Friday, you can reach them through the &quot;Get Help&quot; button on this page.

'''Before class on Friday February 10th: '''


 * Create an account and join this course page, using the enrollment link your instructor sent you.
 * When you arrive on Friday you should already have your username, and you should be able to see yourself enrolled on the Students tab above.
 * Take the training modules listed below.
 * When you finish the trainings, you can practice by introducing yourself to a classmate on that classmate’s Talk page if you like :-)

Here are two additional (optional) references to review that might be helpful: Editing Wikipedia (the last page has a cheat sheet of wiki markup codes!) Evaluating Wikipedia

Today in class we will spend some time thinking critically about Wikipedia articles. We'll discuss authority, Wikipedia's content gaps, and some specific examples related to class.

General:

What questions would you ask to figure out how you know whether a source (any source) is reliable? Credible?

Wikipedia:

Pick one or two of the articles in the list below. Take a look at the article, the talk page, the history of the article page. Take a look at the history and the talk page’s time stamps. As you are exploring this, think about:


 * Who has authority on this page?
 * How is this demonstrated?
 * Who are the people who have made significant / important contributions?
 * What’s the process of information dissemination on wikipedia?
 * What makes something stick?
 * What do you make of the talk page?
 * If you feel like it, put something you’ve been thinking about on the talk page!  Sign with a Pistachiosgreen (talk) 18:41, 10 February 2017 (UTC)

Articles:


 * Sociotechnical System
 * Gender Bias on Wikipedia
 * Algorithm
 * Twitter Bomb
 * Embryonic Stem Cell
 * Science, Technology, Engineering and Mathematics
 * Cybernetics
 * Turing Test
 * Wellesley, Massachusetts
 * Paula Johnson (hey! someone create a talk page!)

General:

How do algorithms fit into this discussion we’re having about *process*? About *authority*? Do you feel information created / disseminated via algorithm is any more or less authoritative? When / why / how?

Do you feel like you are or could be an authority for any of these pages? Any other pages? If not, what would it take to get there?

Week 2
To help us really understand the truth behind: &quot;Wikipedia is the encyclopedia that anyone can edit&quot; - you can familiarize yourself with editing Wikipedia by adding a citation or making a small change to an article.


 * Review the following categories (and sub-categories) on Wikipedia and select an article to update:
 * Category:Wellesley College
 * Category:Presidents of Wellesley College
 * Category:Wellesley College people
 * Add 1-2 sentences to a course-related article, and cite that statement to a reliable source, as you learned in the online training.

Choose an article in the Category:Data mining article list (or possibly another on Wikipedia that you think is relevant to the course). Read through it, thinking about ways to improve the language, such as fixing grammatical mistakes. Then, make the appropriate changes. You don’t need to contribute new information to the article.

Your mission: find or create an appropriate photo, illustration, or piece of video/audio to add to an article related to the course.


 * Before you start, review the Illustrating Wikipedia handbook, or see Editing Wikipedia pages 10–11.
 * When you've reviewed those pages, take the training linked below.
 * When you're ready to start finding images, remember: Never grab images you find through an image search, or those found on Instagram, Tumblr, Reddit, Imgur, or even so-called &quot;Free image&quot; or &quot;free stock photo&quot; websites. Instead, you'll want to find images with clear proof that the creator has given permission to use their work. Many of these images can be found on search.creativecommons.org or on commons.wikimedia.org.
 * If you want to create your own image, graph, or illustration remember:  don't just upload an image to Wikipedia. Instead, upload it to Wikipedia's sister site for images, Wikimedia Commons, then place it in the appropriate article. For instructions, read through the Illustrating Wikipedia handbook.

Week 3
For the final project, you can choose to create a new article or make significant contributions to update an existing article on Wikipedia. If enough students opt in, we will complete this course timeline to look something like this (week 3 - week 8) asking students to:


 * finalize a topic to create or update on Wikipedia;
 * compile a bibliography;
 * start a draft;
 * complete a peer review;
 * move your work live;
 * write a reflection paper.